RELATED APPLICATION

[0001] This application claims priority to U.S. Provisional Application

Nos. 63/374,401, filed September 2, 2022, 63/501,508, filed May 11, 2023, and 63/580,621, filed September 5, 2023, each of which is incorporated herein by reference in its entirety.

GOVERNMENT FUNDING

[0002] This invention was made with government support under N00014- 19-1-2138 awarded by the Office of Naval Research and W912HQ-19-P0052 awarded by the Strategic Environmental Research and Development Program. The government has certain rights in the invention.

TECHNICAL FIELD

[0003] This description relates to a mobile robot having legs for both locomotion and grasping functions.

BACKGROUND

[0004] There are many types of robots that can perform various actions. Some examples of robots include industrial robots, service robots, medical operating robots and the like. Robots can be fixed to a location or be mobile and have applications in various environments, such as industrial, military, and security environments. However, mobility and manipulation functions for robots are often considered separately, each having with independent degrees of freedom (DOF).

SUMMARY

[0005] This description relates to mobile robots having legs for both locomotion and grasping functions, as well as to associated systems and methods of using mobile robots. [0006] In one example, a robot includes a central body portion and a plurality of legs extending outwardly from the body portion. The legs are adapted to perform both a locomotion function for the robot and a grasping function.

[0007] In some examples, each of the plurality of legs includes respective first and second joints. The robot can also include a first actuator coupled to the first joint of at least one leg of the plurality of legs, in which the first actuator is adapted to articulate at least a portion of the respective leg relative to the first joint. The robot can also include a second actuator coupled to the second joint of the at least one leg, in which the second actuator is adapted to articulate at least another portion of the respective leg relative to the second joint. [0008] In a further example, a system can include one or more such robots, in which each the robot includes a communication circuit. The system can also include a remote control apparatus adapted to communicate with the communication circuit of the robot through a communication link (e.g., a wireless or physical link), in which the remote control apparatus is configured to control at least some of the actuators of the robot in response to a user input at the remote control apparatus.

[0009] In another example, a method of using a robot includes controlling at least one drive actuator to move a plurality of legs to implement locomotion of the robot relative to a surface. The drive actuator is coupled to one or more of the legs by at least one drive joint, and the plurality of legs extending from a body portion of the robot to terminate in a distal end portion thereof. The method also includes controlling at least one coxa actuator to move at least some of the plurality of legs to perform a grasping function that is adapted to hold an object in a fixed position relative to the body portion.

[0010] In some examples, the method can also include controlling the robot to climb onto the object and controlling the robot so that at least one leg along one side of the robot extends along a respective side of the object. With the at least one leg along a respective side of the robot, the least one coxa actuator can be controlled to move the at least one leg along the one side of the robot to perform the grasping function and securely hold the object against the robot. The method can further include lifting the robot from the surface while the robot securely grasps the object to retrieve the object.

BRIEF DESCRIPTION OF THE DRAWINGS

[0011] FIG. 1 illustrates an example of a tethered robot.

[0012] FIGS. 2A and 2B illustrate examples of leg mechanisms.

[0013] FIG. 3 illustrates an example of an articulated robot.

[0014] FIG. 4 illustrates an example workspace for the robot or FIG. 3.

[0015] FIGS. 5A-5B illustrate the kinematics of the robot relative to an object onto which the robot can climb and/or grasp. [0016] FIGS. 6A-6G illustrate side views of object retrieval being implemented by an example robot, including a half climb (FIGS. 6A-6D), full climb (FIGS. 6E-6F), grasp and pull (FIG. 6G).

[0017] FIG. 7 is a graph showing an example full climb analysis depicting the climbable workspace versus coxa angle and height (body height and object height).

[0018] FIG. 8 illustrates an example control interface.

[0019] FIGS. 9A-9D illustrate a climb simulation for the example robot of FIG. 3.

[0020] FIGS. 10A-10C illustrate a grasp and retrieve simulation for the example robot of FIG. 3.

[0021] FIG. 11 illustrates experimental results of speed on different terrains.

[0022] FIG. 12 illustrates experimental climbing results for the example robot of

FIG. 3.

[0023] FIG. 13 illustrates example kinematic predictions, simulations and results of half climb, full climb and grasp function.

DETAILED DESCRIPTION

[0024] This description relates to robots, robotic systems and methods in which the same legs are used for both locomotion and grasping and/or manipulation functions.

[0025] Mobile robots can access otherwise inaccessible places, and adding manipulation enables utility beyond inspection and surveillance. In factory settings, mobile robots can lift and position inventory by taking advantage of standard sized pallets.

However, in terrain environments that are sufficiently uneven as to require legs, the grasping tasks are likely to be similarly unstructured.

[0026] This disclosure relates to a robot that uses the same legs for both locomotion and grasping. The robot includes a body portion and a plurality of legs extending outwardly from the body portion. As described herein, two or more of the legs can be adapted to perform both a locomotion function for moving the robot relative to a surface and a grasping function. The locomotion function can vary depending on the intended use environment for the robot. For example, the locomotion function can include walking on a surface and/or swimming within a fluid. As used herein, a grasping function can include grasping a moveable object (e.g., for object retrieval), grasping a fixed object (e.g., for fixing the robot at a position or relative to an object) and/or digging (e.g., within sand, soil, etc.). By using the same legs for both locomotion and grasping can increase the versatility of both tasks. The term manipulation of an object further can include grasping and performing an additional function, such as moving, controlling, releasing or otherwise influencing the object that is being grasped. Robots described herein can also include devices or equipment configured to perform other functions in addition to grasping and/or manipulating objects, such as cutting, welding, sensing, analyzing, probing of such objects, adjacent structures and/or the environment.

[0027] As an example, an example robot has four degrees of freedom (DOFs): drive and lift for left and right pairs of legs. The legs can use a reduced actuation Klann mechanism to provide desired motion. The lift DOF rotates the entire trajectory of the legs, which enables gait modulation, climbing, and grasping functions. This disclosure also demonstrates a method of using the robot in which: a robot that can approach, climb onto and securely grasp an object. For example, after grasping the object, the robot and the object being grasped can then be lifted via a load-bearing tether, such as to retrieve or relocate the object. In some examples, the robots described herein can include one or more sensors (e.g., added to the body, legs, or distal ends thereof) to automate recognition and grasping of objects. Also, or as an alternative, the robot can include auxiliary equipment or devices configured to operate on the object being grasped or another nearby object or structure (e.g., to perform cutting, welding and/or other functions). Additionally, the robot can be scaled for specific terrains and object sizes, with potential application in construction, search and rescue, and object retrieval to name a few.

[0028] As another example, a four DOF legged robot can both walk over and grasp objects. The legs (e.g., reduced actuated Klann legs) can be coupled to the robot body (or frame) by an articulated coxa joint. The extra DOF provided by the coxa joint can more than triple the climbable obstacle height and enables grasping of a range of rectangular object widths. The robot further can be adapted and customized for environments and grasping various object shapes.

[0029] As yet another example, a robot described herein can implement other numbers of DOFs, including six DOFs. Such a six DOF legged robot can include four drive DOFs to generate a periodic walking gait and two lift DOFs to pull legs inward to grasp objects (e.g., tubes, UXOs, extrusion, plates). For example, the six DOF robot can be configured to: walk forward/ backward, point turn right /left, arc right/left, body close/open, right body close / open, left body close I open, and digging. In another example, an articulated crab robot can be configured to have three DoFs on each leg and modified dactyls to grasp objects. Such robot can generate a forward-moving gait and a sideways gait to efficiently search for the UXO in both directions.

[0030] FIG. 1 illustrates a conceptual diagram showing the operational concept of an example tethered robot 10. The tethered robot 10 is configured to perform a method that includes: (1) using legs 11 for walking to an object 12, (2) climbing the object 12 (3) grasping the object 12, and (4) being lifted (or pulled) by a tether 14 while grasping the object 12. For example, the robot 10 takes advantage of the walking ability of legs 11 for controlled walking over potentially uneven terrain. Next, after the robot 10 finds a target object to grasp (e.g., via direct vision by a user, an imaging device, such as a camera, and/or by other sensors). The robot 10 is controlled to place legs 11 on top of an object (referred to herein as a “half climb” shown at 2). The robot 10 is then controlled to climb on top of it until front and back legs 11 are placed on the opposite sides of the object (“full climb”) so that legs 11 can be pressed against obstacle sides with a secure grasp (shown at 3). In some examples, the load-bearing tether 14 can provide a main lift force to retrieve the target object. For example, the tether 14 can suspend the robot 10 from structure 16, such as a crane, a boat, a rotorcraft or a larger robot, to retrieve the object 12 (e.g., samples, essential tools, hazardous materials or other target objects). Because the robot 10 disclosed herein uses the same legs 11 for both locomotion (e.g., walking) and grasping, the object retrieval function can be facilitated.

[0031] The robot 10 can be self-powered having an internal power supply (e.g., battery) and/or power can be supplied through an electrically conductive cable that forms part of the tether 14. Many search and rescue teams prefer tethered robots because the robot 10 can always be retracted. In examples where the robot 10 is small enough to explore confined spaces and can be dragged back with larger object in tow could be especially helpful for clearing blocked infrastructure or search and rescue. Alternatively, the robot 10 can be implemented as a self-positioning end effector for a crane hook would save humans the role of securing loads in difficult to access spots. For example, the robot 10 disclosed herein can be used as marine robots to walk along the sea floor and retrieve environmental samples, hazards such as unexploded munitions, or rare metal nodules have the potential to be both profitable and environmentally friendly. Currently, flying robots have to precisely align a hook or connector to a load, which requires a combination of skill and appropriate weather conditions. A walking and grasping robot, such as described herein, would reduce required precision and enable access to objects that are occluded from the sky by overhanging structures or plants.

[0032] Example embodiments of the robot 10 described herein are different from many other types of legged robots, which can grasp objects in its environment by an attached robotic gripper, in that the whole robot 10 (including its body and legs) can be adapted to grasp the object. That is, rather than reserve some legs for locomotion, the robot 10 uses more legs 11 to contribute to the secure form or force closure of the grip. Unlike in climbing robots, which often require specialized end-effectors, the same legs 11 of the robot 10 will be used like the fingers of a grasper. The legs 11 can have tapered distal end portions, which can be key for secure walking in sand, rocks and other similar terrain.

[0033] Determining the minimum number of degrees of freedom (DOF) of the robot 10 can be an important design consideration for many applications. Fewer DOF makes robots easier to control (and therefore more widely usable in emergency situations such as search and rescue). Reduced actuation (in which parts are driven together) can also make the robot lighter, and thus potentially deploy able from the air. Using a single drive motor, rather than multiple independent actuators, for each leg can also increase performance by reducing required torque-to-weight ratio and decreases cost for robustness because actuators are often the most costly component of a robot. As described herein, the legs 11 of the robot 10 can be implemented as reduced actuation legs 11 that convert continuous rotation to a walking trajectory. There are several forms of reduced actuation legs 11 that can be used for the robot 10. RHex legs are a spoke with variable speed in stance and swing. Wheel-legs have more spokes and typically operate at constant speed. Other types of four-bar mechanisms are possible. Jansen linkages have 10 links, but Klann linkages have only seven links.

Accordingly, several example robots described herein have legs that are implemented using reduced actuation Klann linkages. For example, the robot can include Klann mechanism legs that have been added to the end of a coxa joint to provide an additional DOF. Thus, the linkage design separates the functions of the DOF when the Klann mechanisms are driven the robot moves forward (drive DOF) whereas when the coxa is driven the legs pull inward or outward like a claw (lift DOF), such as shown in the example leg mechanism of FIGS. 2A and 2B. Mechanism Design

[0034] The robot described herein is designed to have compatible degrees of freedom (DOF) for both drive and lift. The drive DOF is responsible for creating a periodic gait trajectory, using continuous rotation as input for efficiency and simplicity. The lift DOF is responsible for raising the legs to climb onto the obstacle and for pulling the legs inward to grasp the obstacle once it has been climbed. In some examples, such as for climbing onto an object, because the left and right halves of the robot need to lift onto the obstacle sequentially, the robot includes two lift DOFs (left and right). The robot is also configured to steer into position, and thus includes two drive DOFs. The robot having four legs thus can be implemented having a total of four DOFs. Other numbers of DOFs can be implemented with robots having different numbers and configurations of legs based on the approaches described herein.

Leg Mechanisms

[0035] FIG. 2A depicts an example of a dual leg mechanism 50 that can implement both locomotion and grasping functions. The leg mechanism 50 provides a useful example of a leg mechanism that can be used to implement each of the legs of the robots described herein (e.g., legs 11 of the robot 10; legs 102, 104, 106, 108 in the example robot 100 shown in FIG. 3). It will be appreciated that the geometry and kinematics of each leg mechanism 50 can be modified from that shown and described according to intended use. For example, the lengths of respective links and/or joint locations can vary depending on objects/surfaces to be grasped and environmental conditions and surface where the robot will be used.

[0036] In the example of FIG. 2A, the leg mechanism 50 includes a dual Klann leg, which can improve the static stability and smoothness with reduced DOF. The leg mechanism 50 includes dual Klan linkages (also referred herein to as legs) 52 and 54 coupled to a coxa plate 56. The coxa plate 56 can be coupled to the chassis (or body portion) 58 of the robot by an articulated coxa joint 60 having an axis orthogonal to the coxa plate. As described herein, the coxa joint 60 can be articulated relative to the body portion, schematically shown at 58, of the robot over an angle (a) based on actuation of a coxa actuator (see, e.g., actuator 150 of FIG. 3). Because the legs 52 and 54 are fixed to the coxa plate 56, rotation of the coxa plate also causes corresponding movement of legs 52 and 54 about the coxa joint. Thus, by controlling the angle a of rotation for the coxa joint, the legs 52 and 54 can be moved upward or downward, such that distal ends 62 and 64 of the legs move outwardly or inwardly (e.g., like a claw) relative to the body portion 58.

[0037] Each of the legs 52 and 54 can have the same dimensions and configuration. For example, the leg 52 includes an arrangement of links shown as n to n. The links can be formed of a rigid material, such as a metal or plastic. Each of the links can be the same material or different materials (and/or coatings) can be used in some examples. Link n is coupled to the coxa plate 56 by rotational joint Oi. Link n is coupled to the coxa plate 56 by rotational joint CL- Link is coupled to the coxa plate 56 by rotational joint Thus, the position of the rotational joints Oi, Ch. O3 is fixed with respect to the coxa plate 56. Additional rotational joints 66, 68, 70 and 72 are coupled between pairs of respective links, such as shown, to provide a cyclic trajectory for the leg 52. The rotational joints 66, 68, 70 and 72 are not fixed (grounded) to the coxa plate (as are joints Oi, O2, O3), and thus will move relative to the coxa plate and body portion 58 during actuation of the leg 52. The leg 54 can include the same links n to n and rotational joints as the leg 52 but is coupled to the articulated joint Oi at an angular offset (e.g., a fixed offset) relative to how the leg 52 is coupled to joint Oi, such as 180 degrees.

As a further example, the rotational joint (?i is an articulated joint, which is driven by a drive actuator (e.g., drive actuator 120, 122, 124, 126 shown in FIG. 3). For example, the drive actuator rotates a shaft, to which the crank arm n is coupled, about the drive motor axis extending through Oi (e.g., orthogonal to the plane of the drawing sheet for FIG. 2A) resulting in a cyclic leg trajectory that will include both stance and swing. For a given direction of walking, the drive actuator can rotate the continuously at a constant speed. In an example, each leg pair 52, 54 is driven together by respective crank arms n at a 180 degree offset to form the dual Klann legs. Through the link lengths from n to n and the position of the rotational joints Oi, O2, O3, the position vector of the end effector r can be determined from Eq. 1. r = r ₁ + r ₃ + r ₄ + r ₇ (1)

[0038] The example gait shown at 76 is a “locked gait” where the coxa angle a is fixed at 0°. In other examples, the gait can be fixed at different coxa angles or the coxa angle can be variable during the gate. The coxa actuator (e.g., actuator 150 of FIG. 3) can be configured and controlled to adjust the coxa angle over a range of angles, such as ranging from -90 to +90 degrees relative to a zero coxa angle (e.g., a 180 degree range). Gait Optimization

[0039] For the example closed-chain leg mechanism, a design goal of its generated single gait can be to walk smoothly and swing across small obstacles like pebbles in the uneven terrains. The Klann linkage mechanism can be configured to optimize the gait shape for efficient walking on a given surface.

[0040] An example definition of the gait shape is shown at 80 in FIG. 2A. Pi and P ₂ represent the liftoff point and the touchdown point having a phase difference it, which divide the swing phase and the stance phase. For the example of one single trajectory, the gait parameters Pi and P ₂ can be configured to satisfy the following criteria: (a) Stride length P1P2 should be as horizontal as possible so that both stance phases of front and back legs would be co-linear; (b) Stride length P1P2 should be large enough to achieve fast speed; (c) Swing height P3P5 should be as long as possible to swing across obstacles; and (d) Stance variation P4P6 should be relatively small to reduce moving vibration. The objective function is shown as Eq. 2, where coefficients are chosen as a = -1, b = 100, c = -10, d = 10. The optimization can be performed to realize all requirements; however, every variable may contribute to the gait shape. There is a trade-off between stride length, swing height and the stance variation, which means it is impossible to fix one characteristic and then enlarge another. Example specifications of optimized links are shown in Table. 1.

Table 1 - Example of the leg dimensions

[0041] As a further example, by using the sequence quadratic program, the optimized gait and gait parameters are generated: 1 2 = 47.9 mm P3P5 = 14.8 mm, P Pt, = 5.4 mm, arctan = 0. Because the stance straig &htness i = 11.3% and the stance variation is only 5.4 mm, P i P is the approximate stance phase in the following kinematic analysis. In other words, the trajectory under P1P2 would be neglected. Other gate parameters can be determined in other examples.

[0042] FIG. 2B depicts another example of a leg mechanism 90 that can be used in a robot to implement both locomotion and grasping functions. In the example of FIG. 2B, the leg mechanism 90 has a gear reduction of 3:1 and a 20 degree helical gear drive. Other gear reduction and gear drive configurations could be used. In an example, the leg mechanism can provide a motor stall torque of about 7.4 kg/cm at 5A and have a gear output of about 22.4 kg/cm (2.19 N/m) at 5 A. Such configuration further can provide an inward leg force of about 50.7 N at 5A with a horizontal step force equivalence.

Coxa Joint Mechanism

[0043] It will be evident that there are many challenges to successfully grasp a specific object when operating in various terrains. While the example dual Klann leg mechanism 50 of FIG. 2 has a high level of stability, it might be unable to overcome taller obstacles without also including the lift DOF (e.g., implemented by the articulated coxa joint 60). Furthermore, for grasping, the coxa joint 60 should be adjustable and powerful to apply sufficient normal forces such that friction between the object and the dactyls will be enough to secure the desired pay load. As described herein, there are three main functions of coxa joints in relation to object retrieval: the front legs can step on a higher platform, the body chassis can be raised higher when all four legs are on the ground, and the robot can grasp a wider range of objects.

[0044] An example mechanical structure of an articulated robot 100 is shown in FIG. 3, which is mechanically adapted to perform both locomotion and grasping functions. In the example of FIG. 3 the robot 100 is implemented as a walking claw robot that includes four leg mechanisms (also referred to herein simply as legs) 102, 104, 106 and 108 operatively coupled to and extending from a central body portion 110 to terminate in respective distal end portions 130, 132, 134 and 134. As shown, each of the legs 102, 104, 106 and 108 can be implemented as including a pair of legs (e.g., dual legs), such as to afford increased stability for locomotion on a surface. In an example, each of the legs 102, 104, 106 and 108 can be implemented as a reduced actuated Klann leg, a dual-reduced actuated Klann leg (e.g., leg mechanism 50), or other form of linkage. While the robot 100 shown in FIG. 3, includes four legs, other numbers and configurations of legs can be used in other examples. For example, at least six legs or three dual Klann legs are needed to implement an alternating tripod gait. However, to provide for left right and front back symmetry, four dual legs are used in the example robot 100. The additional legs help distribute weight and prevent the robot from sinking into substrates. In addition, a support triangle can be maintained even with a lifted leg. Each of the legs 102, 104, 106 and 108 can be implemented as the same size and configuration of leg or, in other examples, different legs can be implemented differently. With the configuration and arrangement of legs shown in FIG. 3, the robot 100 can travel along a walking trajectory having a direction indicated by an arrow at “D.” For ease of explanation, the description of FIG. 3 refers to legs 102 and 108 as front legs and legs 104 and 106 as rear legs. Though, it is understood that front and rear are relative terms.

[0045] Each of the 102, 104, 106 and 108 can be implemented as a linkage including an arrangement of links and rotation (or pivot) joints, such as disclosed with respect to FIG. 2A or 2B. Some of the rotation joints are fixed (e.g., grounded) with respect to the body portion 110, and one of the fixed rotation joints (e.g., a respective drive joint) 112, 114, 116 for each of the respective legs 102, 104, 106 is an articulated joint. The drive joint for the leg 108 is not visible in the view of FIG. 3, and it is understood that the leg 108 has a similarly configured drive joint as the other legs.

[0046] A drive actuator 120, 122, 124 and 126 is coupled to each drive joint 112, 114, 116 to provide for articulation of the joint and associated leg 102, 104, 106 and 108. For example, the drive actuators 120, 122, 124 and 126 can be implemented as rotary DC motors having a shaft that rotates responsive to a drive control signal (e.g., from a motor controller). The speed and power for each motor can vary depending on the application and environment in which the robot is to be used. In some examples, the actuators 120 and 122 are driven by a first control signal to provide a first DOF, and actuators 124 and 126 are driven by a second control signal to provide a second DOF. This arrangement thus allows the four legs to implement two drive DOFs for forward and backward walking and turning. In other examples, each of the actuators can be driven independently. In response to activating the drive actuators, the distal end portion (e.g., foot or end effector) 130, 132, 134 and 134 of each leg 102, 104, 106 and 108 moves along a gait trajectory according to the geometry of the links and joints implemented for each leg (see, e.g., FIG. 3). In some examples, the robot 100 implements foot trajectories of a 50% duty cycle (e.g., half of the legs are in the stance phase and half are in the swing) and at a constant drive speed.

[0047] The distal end portions 130, 132, 134 and 134 can be configured as end effectors having different functional and/or material properties that can be selected according to application requirements. For example, the distal end portions 130, 132, 134 and 134 can be configured as pointy dactyls, be rubbery or compliant, shaped as rigid spears, include bristles or barbs, be fork shaped or curved. Other shapes and material properties can be used in other examples. As another example, the robot 100 can include grasping legs in combination with a grasping gait to enable the robot to anchor to the ground at every step, which can help preventing overturning and allowing climbing over rocky terrain.

[0048] In yet another example, end effectors at one or more distal end portions 130, 132, 134 and 134 can include tools for various purposes. Thus, different tools can be implemented on the robot at desired tool locations depending on application requirements. Such tools can extend from the distal end portions, such as extending in a fixed spatial relationship (e.g., permanently) or be retractable relative to the distal end portions 130, 132, 134 and 134 (e.g., by an actuator, such as linear or rotary actuator). Also, or as an alternative, tools can be mounted to the body portion of the robot 100.

[0049] As an example, one or more of the distal end portions 130, 132, 134 and 134 include respective exothermic rods extending from the distal end portion(s) and adapted for welding and/or cutting. For environments lacking oxygen (e.g., marine and space applications), the robot 100 can also include a source of oxygen or air configured to supply oxygen or air to each exothermic rod, such as a through a conduit coupled between the source and the exothermic rod (e.g., within or along the tether coupled between the robot and a remote station).

[0050] Other tools that can be implemented as end effectors at distal end portions 130, 132, 134 and 134 or implemented on the body portion include probes and/or sensors. For example, a probe can extend from the distal end portion, in which the probe is configured to collect one or more samples from a target. The target can be the terrain and/or an object, and the robot can be configured to grasp the object (or terrain) to fix the position of the robot with respect to the target while the robot obtains the sample. The robot thus can collect one or more samples, which can be analyzed on the robot and/or be returned to the remote station for further analysis. As one example, the samples can include sediment sample(s) from underwater terrain (e.g., floor or beds) or from an underwater structure (e.g., supports for a bridge or pier), which can be analyzed to assess scour and/or other conditions. In some examples, a plurality of robots can be deployed to obtain samples from different respective locations.

[0051] Also, or as an alternative, a robot can implement other tools as end effectors at distal end portions 130, 132, 134 and 134 or implemented on the body portion, which can include a netting system, magnets or other mechanism that can attach to various objects. [0052] For each leg to be used for grasping, the robot 100 also includes an articulated coxa joint, shown as coxa joint 138 for the leg 102 (coxa joint for leg 108 is not visible in FIG. 3). Each coxa joint 138 provides an additional degree of freedom to enable the legs 102, and 108 to implement both locomotion and/or grasping functions. For example, the robot 100 includes a respective coxa plate 140, 142, 144 and 146 for each of the legs to be used for grasping and locomotion.

[0053] Each coxa plate 140 and 146 can be coupled to the body portion 110 (e.g., a frame) by a respective articulated coxa joint 138. Each coxa joint 138 can include a shaft that is coupled (directly or indirectly) to a coxa actuator, shown as 150 and 152. Each coxa actuator 150, 152 can be coupled to drive one or more respective coxa joints a coxa angle, such as described with respect to FIG. 2 A or 2B. The coxa actuators 150 and 152 can be implemented as rotary DC motors having shafts that rotates responsive to respective lift control signals (e.g., from the motor controller). Other types of actuators and motors can be used in other examples. To enable grasping function to be performed by one or more of the respective legs 102, 104, 106, 108 (e.g., responsive to rotation of respective coxa plates), each of the legs is likewise coupled to a respective coxa plate. For example, the respective drive joint 112, 114, 116 and 118 and at least one other fixed rotation joint of each respective leg 102, 104, 106, 108 are coupled to the respective coxa plate, such as described with respect to FIG. 2 A or 2B. [0054] In the example of FIG. 3, the coxa plates 142 and 144 for the rear legs 104 and 106 are fixed (not adjustable by articulated coxa joints) with respect to the body portion. While for simplification of explanation, the example robot 100 includes articulated coxa joints only for the front legs 102 and 108, in other examples, each of the legs 102, 104, 106 and 108 can include articulated coxa joints, such as to enable grasping between opposing front and rear legs. In such an example, the robot 100 includes a coxa actuator (e.g., a rotary motor) for each respective leg to provide for independent control of grasping functions for each leg 102, 104, 106 and 108. Alternatively, a given coxa actuator 150, 152 can be coupled to drive more than one coxa joint such as to provide for synchronous grasping functions by more than one leg.

[0055] As an example, the coxa actuator 150 can be operatively coupled to coxa joint 138 of opposing leg 102, such as through an arrangement of gears, shafts or other mechanical couplings. The other coxa actuator 152 similarly can be operatively coupled to coxa joint for opposing leg 108, such as through another arrangement of gears, shafts or other mechanical couplings. The number of coxa actuators and coxa joints can vary depending on the number of legs as well as the manner and type of grasping functions to be implemented.

[0056] In some examples, a gear box 160, 162 can be coupled between respective coxa actuators 150 and 152 to transmit rotational transmit rotational power from the coxa actuator to the respective coxa joints. In some examples, the gear box 160, 162 includes mechanisms mechanically configured to hold (e.g., lock) the respective coxa joint (or joints) and coxa plates 140 and 146 at a fixed angle relative to the body portion 110 in the central body portion absence of rotation by the coxa actuator. For instance, each of the gears include a worm gear (e.g., extending orthogonally to the axis of respective rotary actuators 150 and 152) having threads along an elongated body that meshes with wheel which is drive by a coxa actuator, and thus is adapted to lock the worm gear in a fixed position in the absence of rotation by the respective coxa actuator. In this way, each coxa plate 140 and 146 can rotate a desired angle relative to the body portion 110 (about an axis extending through the respective coxa joint) responsive to actuation of the respective coxa actuator 150, 152 to thereby lift respective front legs 102 and 108 upward or downward relative to the body depending on the direction of actuation about the coxa joint. For example, the front legs 102 and 108 can urge an object into contact with an underside 154 of the body portion 110 and/or to contact with the rear legs 104 and 106. In some examples, a rigid catch (e.g., one or more rigid finger, plate or other protruding structure) can extend outwardly a distance from the underside 154 of the body portion 110 against which the legs can hold an object responsive to rotating the coxa joint to move the legs inwardly beneath the body portion 110. For instance, a plate or series of fingers can extend orthogonally from the underside 154 of the body portion 110 a distance at least equal to one half the diameter of the object being retrieved. The catch may also have a surface facing the leg or legs being used to grasp the object that is curved to match a curvature of the object being grasped. In addition to retrieval of objects, the robot can also be used for pick and place operations, such as for construction and/or moving unexploded ordinances or other potentially hazardous objects.

[0057] As a further example, the robot 100 can include one or more sensors, such as automated with dactyl sensors to provide force or proximity sensing to control grasping functions. Other sensors can be used, such as rotary encoders, strain sensors, pressure sensors, LIDAR, temperature sensors, position sensors (e.g., global positioning sensors), Hall-effect sensors and magnets, and the like. Each such sensor can provide sensor data, which can be stored locally on the robot and/or communicated to the user via a communication link, to automate or otherwise facilitate controlling robot functions. The communication link can be wireless or physical (e.g., conductive wire or optical fiber) within or forming part of a tether coupled between the robot body and a remote station. Once automated, teams of such robots could descend from a single spreader bar to coordinate automated lifts of large objects. To establish form closure as well as force closure, the first lift could be small, just enough to pass rigging under the target object. Even more intelligent control can be implemented to enable small crab-like robots to search an area for specific objects, and then send up buoys or quadcopters for later collection when convenient.

[0058] Also, or as an alternative example, such as for marine or other applications, load sensing (e.g., implemented by respective force sensors, such as load cells) in the legs 102, 104, 106, 108 can enable the robot 100 to exploit transient currents often available in surf zones for low-power fast punting gaits on smooth ground and/or for wave-assisted climbing (e.g., if stuck). The same (and/or different) sensors can also be used to classify the substrate, including embedded munitions, which can be grasped for retrieval (e.g., in marine or battlefield environments). Sensors embedded in the legs 102, 104, 106, 108 will enable a responsive gait to take advantage of hydrodynamics and search for footholds among small rocks. These sensors can also provide tactile data on terrain geometry (e.g., roughness, convexity, slope) and forces (e.g., stiffness, stickiness, friction). The tactile data can be evaluated by a processor (on the robot and/or remotely) executing instructions programmed to help classify partially buried munitions (simulated by metal cylinders for our planar tests). Other types of sensors can be used in other examples, such as configured to measure environmental conditions and/or characteristics of the object being investigated and/or retrieved.

Kinematics

Klann Linkage Kinematics

[0059] To show the value of the coxa joint in the example robot described herein, the following will compare the kinematics of the robot when the coxa is “locked” (e.g., the coxa angle is fixed at 0°) and when the coxa is active. For example, when the coxa is active, the coxa actuators (e.g., lift DOF actuators) are configured to rotate the dual Klann legs about the coxa joint over a range of angular motion, such as from 90° clockwise to 90° counterclockwise. This motion results in a larger workspace, such as shown in FIG. 4, when using an active gait to find favorable climbing steps. In FIG. 4, the active Klann gait (lift DOF) is traced in by a line, shown at 402, with example stride lengths throughout the range of possibilities. The locked gait, shown at 404, is the only possible gait for the robot when it is in its locked position (Drive DOF). The locked robot has limited locked gait height (14.8 mm). When the Lift DOF enables front legs to step on higher objects, an active gait height is produced, which can be more than one order of magnitude (e.g., about 20 times) greater than the locked gait height.

[0060] In addition to expanding the workspace for the robot, the active coxa joint also rotates the Klann trajectory which affects walking behavior. For example, when the stance phase (P1P2) of the trajectory is at a different angle for the front and rear legs, adaptive gaits can be used for different environments that can affect speed, moving direction and potentially cause mechanical vibrations. At the locked position, the stance phases are co-linear for front and back legs which is expected to be preferred for stability and speed when walking on flat ground. On other terrain, being able to create an inward trajectory might help the robot “grasp the ground”, such as for pliant surfaces (e.g., sand, gravel, dirt and the like). Therefore, the robot can be configured to operate at various coxa angles on different terrains. Kinematic Analysis

[0061] In order to demonstrate that a robot configured according to the subject disclosure obeys expected kinematics, the kinematics can be analyzed. This analysis can also be inverted via inverse kinematics to scale a robot to grasp objects of a desired size.

[0062] FIGS. 5A-5B illustrate the kinematics of the robot relative to an object onto which the robot can climb and/or grasp. FIG. 5A shows kinematics with a locked coxa joint, and FIG. 5B shows kinematics with an active coxa joint. From the geometry, the rotation joint O2 on back linkage is considered as the lowest point of the central body to clear the top when coxa joint rotates clockwise an angle (coxa angle is referred as a). The locked and active full body height (e.g., where a - 40°) are shown in FIGS. 5A-5B. For example, FIGS. 5A-5B show the obstacle height, h, the robot can fully climb onto with either locked (FIG.

5 A) or active (FIG. 5B) coxa joint. The body height, H, can be much higher with an active coxa, and the grasp length is adjustable. FIGS. 5A-5B are shown with horizontal ground rotated into the body reference frame defined by FIG. 4.

[0063] For the climbing and grasping tasks, such as shown in FIGS. 6A-6G, there are three main kinematic issues to address. First, the robot has to be able to put its legs on top of the obstacle, which is referred to as a “half climb” (FIGS. 6A-6D). Second, the robot needs to be able to lift the body high enough to clear the top of the obstacle so that it can walk the legs across the obstacle. This is achieving a “Full Climb” (FIGS. 6E- 6F). Finally, the distance between end effectors needs to be adjusted to match the object, achieving sufficient “Grasp” so that the tether can pull the object from the ground (FIGS. 6F-6G). In the examples of FIGS. 6A-6G, the configuration of the robot is according to the specifications of Table 1 (above). Of course other configurations can be used in other examples to achieve different kinematics.

Half Body Climb

[0064] Referring to the example robot of FIGS. 6A-6D, the maximum height of half climb depends on gait height. In an example, the locked robot has a gait height P3P5 of about 14.8 mm. To stand on a higher platform, the first coxa joint lifts the first dual Klann leg up, while the other three end effectors stand on the ground, maintaining a support polygon. The active gait height is the height of P2 with respect to the locked stance phase. Compared to the locked gait height, the active gait height is up to 280 mm when the coxa joint rotate 90° counterclockwise, such as shown in FIG. 4. After the first leg is placed on the object, the second front dual leg will lift to be placed on the obstacle. The initial position will be oblique to the front face of the object, and during climbing, the robot can be maneuvered into a better position for lifting using the Drive DOF.

Full Body Climb

[0065] As shown in FIGS. 6E- 6F, a full climb is completed when the robot walks across the object until front and back legs are on the opposite side of the object. If front legs can reach the top, but then the central body cannot clear the top of the obstacle from the ground, the robot will be able to make a half climb but not a full climb. To successfully full climb, the whole chassis should be higher than the object. Therefore, the ability to clear the top is geometrically determined by the lowest point of the chassis (the lowest point is referred as the body height H). No matter how many unnecessary parts of the body chassis can be eliminated to heighten the body, at least Klann linkage points need to be retained for the mechanical design. Thus, the basic Klann linkage analysis can determine a best full climb ability, assuming the chassis does not have extra material on the bottom to interfere with climbing.

[0066] The body height (H) can be changed by both the coxa angle CW (a) and the obstacle height (/r), since the coxa joint can push front legs inward to heighten the body, and the obstacle itself can raise the robot when front legs step on it. The body height is expressed as Eq. 3. The links n, n, rt, n are fixed distance between points, whereas r< is changed when the coxa joint rotates. Thus, is fixed based on the cosine law, and 0i and 63 can be expressed as 62 =fi(a) and ft =fi(a,h). where Li is the length of n

[0067] Since P1P2 is the approximate stance phase, Pj- , is considered as the point when back legs touch the ground (Ptb refers to the Pi on the back gait. Pif refers to the P ₍ on the front gait, i = 1 or 2). However, for front legs, either Pif or P2f is possible to contact top of the object. If ft < ft, Pif will be the contact point (FIG. 5A), otherwise, P2f will be the contact point (FIG. 5B). ft is the angle between the ground and PifP2f- 65 is the angle between horizon and P//P2/. To successfully clear the top of the object, the body height should be large than the obstacle height (Eq. 4). Before ft + ft + ft reaches TT/1, when a becomes larger, H is larger if h is fixed. However, it is not always true that a bigger coxa angle is preferred due to problems, such as unsuitable walking gait and unstable support polygon. Slowing down the motor speed can mitigate the vibration caused by bad gaits. To achieve static stability, the center of mass (CoM) lies in the support polygon defined by the end effectors. Thus, the CoM projection should be larger than stance projection (Eq. 5), where Lb represents the length of re, which is the distance between CoM and Pzb, Ob is the angle between re and PthPih.

[0068] FIG. 7 is a graph showing body height (//) vs obstacle height (h) versus coxa angle (a) for the example robot of FIG. 3 according to the specifications of Table 1.

Different geometries can be used in other examples to provide different workspace areas and climb heights from that shown in FIG. 7. FIG. 7 depicts an available workspace, shown at 602, in which the top line 604 represents a maximum climbable height in every coxa angle from 0° to 90° CW. Though body height is limited by invariable Li, the maximum active climbable height is 136.4 mm (76.6% robot height) when the coxa angle is 53.3°. In contrast, the workspace areas, shown at 606 and 607, represents the full climb failure. According to Eq. 4 and Eq. 5, full climb failure above the dashed line (area 607) is lack of body height, while failure below it (area 606) is that CoM is out of support polygon. To verify the full climb analysis, in following sections, Webots simulation and physical experiments were conducted on adjustable stairs with different coxa angles. The line 608 represents the simulation result. The line 610 depicted the experimental results. The star shows the kinematic prediction when a = 40°, such as shown in FIG. 5B.

[0069] In general, the half climb mainly relies on the gait height so that the active prediction is 280 mm, whereas the locked prediction is only 14.8 mm. For the full climb, though the body height at 0° is 105.7 mm, the locked full climb is limited by a failed half climb. Thus, the locked full climb prediction is the same with locked half climb (14.8 mm). In contrast, with the coxa joint, the robot can reach 136.4 mm when raising the body by pressing front legs down. Different geometries can be used in other examples to provide different workspace areas and climb heights.

Grasp and Pull

[0070] For the example robot 100, grasping depends on the grasp length PifPib- The locked Klann robot has limited ability to grasp. Even if the robot climbs onto an obstacle that is exactly the Grasp Length Max, and the legs drop down on either side, the robot has little ability to pull the legs inward since they are driven together. Even if the front and rear legs were driven separately, the maximum theoretical grasp range would be limited by the stride length (47.9 mm). However, the number of degrees of freedom even without the coxa would be four and the climbing height would not be increased.

[0071] The Lift DOF also changes the grasp length, which enables the legs to press into the sides of the object. Based on the example grasp kinematics in FIG. 5B, the maximum grasp length is 371 mm (89% robot length) and the minimum grasp length is 167 mm (40% robot length). Thus, the range of object sizes that are graspable for the example robot is 204 mm. The self-locking driving system on the coxa joint holds tightly without any input power due to the thread-locking of the worm drive system. After the robot grips tightly on the object, the tether can be pulled and object retrieval is completed, such as shown in FIGS. 6G.

Robot Assembly

Example Hardware Components

Example Actuators and Gearbox

[0072] To avoid complexity in the control system and maintain sufficient power in continuous rotation, rotary DC motors can be implemented as the actuators because of their simplicity, high torque, and favorable size. In an example, the drive actuators 120, 122, 124 and 126 can be Pololu 3203 motors (e.g., having a gear ratio 20.4:1, 12 V, 500 RPM, 7.4 kg-cm) and the coxa actuators 1 0 and 152 can be implemented as Pololu 4748 motors (e.g., having a gear ratio 10:1, 12 V, 1000 RPM, 4.9 kg-cm). Between the Pololu 3203 and dual Klann legs, drive-gearboxes (e.g., gear ratio 3:1) are used to produce enough torque to perform the periodic gait. With the Pololu 4748 paired with the coxa joints, worm-gearboxes are chosen as they are non-backdrivable and can achieve high gear reductions in a small space (e.g., gear ratio 40: 1), allowing the robot to hold its stance or grip without further input power. Other types of actuators can be used in other examples.

Example Controller and Driver

[0073] As an example, the controller for the robot 100 can include an Arduino mega and two dual H-bridge PWM motor drivers (e.g., 12 V). In an example, the robot is powered by a 12 V power source. Other motor controllers and power sources can be used in other examples to control the respective actuators, such as in response user input commands (e.g., provided by a control interface through a communication link). For example, a robot operator is able to control actuation of the robot manually through user inputs provided with a joy-stick controller via a RC transmitter and receiver. Other types of user interfaces can be used in other examples. An example wireless joystick control interface is shown in FIG. 8, which can communicate with the robot through a wireless communication link. In other examples, the control interface can be coupled to the robot through a physical communication link (e.g., electrically conductive or fiber optic cable) within or coupled to a tether that is coupled to the robot, such as disclosed herein.

[0074] An example joystick control strategy is also shown in FIG. 8: The right stick controls the Drive DOF, moving the robot in four different directions (forward, backward, left and right). The left joystick controls the Lift DOF, moving the target leg up or down. The vertical axis of the left stick is used to select which side’s coxa is adjusted.

[0075] Additional mechanical improvements or features that could be implemented in any robot described herein can include one or more of the following: increase effective force at dactyl tip, which can be provided by using increased motor torque, higher gear reduction, reduced dactyl surface area/tip geometry; improved wear resistance of key components, including at leg linkages and gearbox housings; and/or implement ‘netting’ system to improve pickup operations with only one dactyl set.

[0076] Also or as an alternative, system improvements and features that could be implemented in any robot described herein can include one or more of the following: integrate feedback capabilities, which can include onboard encoders, 3 axis accelerometer, and/or standardized stance for different operations; integrate motion modeling and route planning; and/or integration of the robot into an existing ROV system.

Example Fabrication

[0077] As an example, the main chassis (e.g., body portion 110), several of the gearboxes and all links can 3D printed in PLA. The leg gear box utilizes brass gears and bushings. Nylon washers are placed be- tween every fastener and every mating surface of the Klann linkage to reduce friction. The weight of four dual Klann legs is 1.12 kg; adding two coxa joints increases the total weight up to 2.03 kg (181% weight of four dual legs). Specifications of the articulated Klann robot and the length of Klann links are shown in Table 1.

Performance Simulation

[0078] To verify kinematic predictions above, a Webots-based simulation was conducted to test the ability of the object retrieval. Environment parameters were set as follows: gravity coefficient 9.8 m/s ² , material density of the robot 1250 kg/m ³ (e.g., polylactide (PLA)), mass of Pololu 3203 (85 g), mass of Pololu 4748 (175 g), friction coefficient between the robot and ground 0.5, friction coefficient between the robot and the obstacle 0.8, weight of the rectangular object 1 kg, constraints of revolution joints. All component models were input into Webots, then assembled together with six motors as drive DOFs and lift DOFs. FIGS. 9A-9D illustrate a climb simulation for the example robot of FIG. 3 using Webots. Since Webots cannot compute complex contact and constraint problems, if the motor speed is too fast, the simulation will have failed results. As a result, the motor speed was set as 2 rad/s in Webots, however the motor speed was 11 .3 rad/s when it walked on the lab tiles at 0° (Walking speed is 0.173 m/s. One stride length is 47.9 mm. Each rotation period contains two stance phases.).

[0079] To evaluate of the climbing performance, the robot was tested by half climbing onto an object, and then full climbing over it. The height of the artificial stair was adjustable ([5:1:20] cm) with a fixed width of 25 cm and a length of 50 cm. For the locked robot, it could only half climb 2 cm and then full climb 2 cm. Full climb was limited by a failed half climb. To test the active robot, the robot first needed to approach the object properly. Specifically, the front face of the object was 70° angle from the moving direction as FIG. 9A. After moving the robot to its ideal staring point, the half body climb began, which was divided into two parts: lifting and placing the first front dual leg, and then repeating this process with the second front dual leg. According to kinematic analysis, a were set as 90° CCW to achieve the best half climb. Active full climb was tested at different coxa angle [0: 10:90]°. In contrast to the locked result, the active robot could half climb up to 20 cm (1 12% robot height). The active half climb was only 71 % prediction height, since a support polygon was not stable while lifting one front leg. The maximum active full climb was 13 cm (73% robot height) when a was 50° and 60°, shown in the line 610 in FIG. 7. Since the kinematic analysis only concerned Klann linkages, simulation results had tradeoff to kinematics before 50° due to the additional chassis. However, it was better than predictions after 50° when CoM began to get close to the support polygon, since less vibration caused by low motor speed would mitigate problems with instability.

[0080] FIGS. 10A-10C illustrate a grasp and retrieve simulation for the example robot of FIG. 3. In the simulated grasping test, rectangles (fixed length 50 cm, fixed height 13 cm, width [15:1:38] cm) were set under the robot for further grasp. With the coxa angle manually controlled from 0 to 90° CW, the robot could securely retrieve the object from 16 cm (38% robot length) to 29 cm (69% robot length). The available grasp range was 13 cm. The minimum grasp length was close to the prediction (16.7 cm). However, the maximum length had some tradeoff to the kinematics (37.1 cm). The main reason of the deviation was that when rotating small coxa angle CW, it would be hard for the robot to maintain at least a parallel gripper. Thus, the friction was insufficient for a secure grasp. Changing the inner shape of end effectors or adding high friction material could solve this problem.

Example Experiments and Results

Evaluation of Speed

[0081] In the speed test, the robot (e.g., the robot 100 of FIG. 3) was fully charged by the maximum voltage (12 V) to move forward in different flat terrains, such as lab tiles, carpet (polypropylene), a yoga mat (EVA foam) and a bed of pebbles. The bed was 5 cm depth full of pebbles with diameter below 2 cm. Average speed was tested for 10 seconds for the lab tiles and carpet, 8 seconds for the yoga mat and 6 seconds for pebbles because of different sizes of testing environments. At least three tests were completed on each terrain. To find how coxa joints affected the speed, the robot was tested with both coxa joints rotated to 15° CCW, 0° (locked), 15° CW, and 30° CW. More extreme coxa angles caused vibrations and low body chassis to contact the ground. The speed results for locomotion of the robot over different terrains are shown in FIG. 11. In FIG. 11, a star indicates the maximum speed in each terrain.

[0082] As shown in FIG. 11, the robot was fastest overall on the smooth lab tiles.

Then, the overall speeds on the yoga mat (EVA foam) and carpet (polypropylene) were close, ranking the second and the third. Pebbles were the worst, since the legs can slide backward in the granular media. If only speed is considered, 30° CW is the best angle for lab tiles, 15° CW for carpet, 0° for both yoga mat and pebbles. In addition, 15° CCW was not good for all terrains due to low body height contacting the ground. Big coxa angles CW were also not ideal on the yoga mat and pebbles because the swing phase of the gait became more horizontal as the coxa angle CW became larger. This would cause the robot to be blocked by large pebbles or by foam when the leg sank a little into the yoga mat. As a result, a vertical swing phase with small coxa angles was more suitable for pebbles and yoga mat, such as 0° and 15° CW. However, 0° was not good for lab tiles and carpet. The robot would move faster due to bigger friction from dig motions around the touchdown point P2, when rotating a bigger coxa angle CW (15° CW or 30° CW). Thus, the coxa is valuable in adjusting the robot for different terrains since there is no one position that is preferred for all different types of terrains.

[0083] In addition to the speed, the COT (Cost of Transportation) was 7.06 when the robot walked on the tiles at 0°, which indicated the energy efficiency of the Klann robot. It was close to the animals’ equivalent data, though friction of rotational joints influenced the walking ability.

Evaluation of Climbing Performance

[0084] To evaluate of the climbing performance, the robot (e.g., the robot 100 of FIG. 3) was tested by first half climbing the adjustable artificial stair, and then full climbing, like the simulation tests. The top surface of the stair had enough friction for legs to step on without sliding. For the half climb at 90°CCW, the approach must be oblique to the front face of the object. When the first leg was placed onto the platform, the other front leg must have enough space to lift without hitting the object. For the full climb, coxa angles [0:10:90]° were tested. We tested the locked Klann robot and the active Klann robot three times for each obstacle height. Tests over 1 minute are considered as failure.

[0085] FIG. 12 shows the experimental results on climbing performance. In FIG. 12, successful climbs are shown at 1202 and failed climbs are shown at 1204. The active full climb only shows the result when a is 50°. Other experimental data with different coxa angles can be found in FIG. 7. The locked robot succeeded in half-climbing up to 10 mm. For higher obstacles, the end effector kicks the object without lifting front legs up. In fullclimbing, the locked robot could climb up to 10 mm as well, which was limited by the locked gait height. This is lower than the simulation result 2 cm, since PLA deformation would cause the gait shape inconsistent with the optimized gait in FIG. 2 A. Thus, lower the stance height. Overall, the active robot outperformed the locked robot in both half climbing and full climb. The active half climb was up to 190 mm, though it was smaller than the prediction (e.g., about 280 mm) due to the same reason with the simulation (unstable support polygon). The first lifted dual leg would be closer to the ground than the kinematic analysis, thus resulting some offset. Then, active full climb results with different coxa angles were shown in the blue line in FIG. 7. The active full climb was up to 120 mm at 50°, approximately to the prediction (e.g., about 136.4 mm). Though it was worse than the simulation due to vibrations caused by high speed DC motors, the overall trend was close to simulation and the kinematic predictions. The kinematic prediction neglected chassis and PLA deformation, which would lower the actual climbing ability. Adjustments to chassis design and rigid material could mitigate this, but still the predictions are reasonable.

Evaluation of Grasping

[0086] To evaluate the ability to grasp objects, the robot gripping was directly tested on different rectangular boxes. Though the horizontal stride length was 47.9 mm, the locked robot was not capable of gripping because front and back legs were not driven separately. Coxa joints enabled the robot to grasp objects with width from 180 mm (43% robot length) to 300 mm (72% robot length) by rotating coxa joints from 0° to 90°. This is comparable to the predicted grasp length from 167 mm to 371 mm. The minimum grasp length was close to the prediction. However, the maximum grasp was worse than predictions. Maximum grasp had the same problem with the simulation: small coxa angles did not maintain a parallel gripper, thus upward force was insufficient. Kinematic predictions, simulation and experimental results are shown in FIG. 13.

[0087] In view of the foregoing, robots, robotic systems and methods are described to use the same legs for both locomotion and grasping and/or manipulation functions.

[0088] As used herein, the term “and/or” can include any and all combinations of one or more of the associated listed items. As used herein, phrases and/or drawing labels such as “X-Y”, “between X and Y” and “between about X and Y” can be interpreted to include X and Y.

[0089] It will be understood that when an element is referred to as being “on,” “attached” to, “connected” to, “coupled” with, “contacting”, “adjacent”, etc., another element, it can be directly on, attached to, connected to, coupled with, contacting, or adjacent the other element or intervening elements may also be present. In contrast, when an element is referred to as being, for example, “directly on,” “directly attached” to, “directly connected” to, “directly coupled” with, “directly contacting”, or “directly adjacent” another element, there are no intervening elements present.

[0090] Spatially relative terms, such as “under,” “below,” “lower,” “over,” “upper”, “proximal”, “distal”, and the like, may be used herein for ease of description to describe one element or feature’s relationship to another element(s) or feature(s) as illustrated in the figures. It will be understood that the spatially relative terms can encompass different orientations of a device in use or operation, in addition to the orientation depicted in the figures. For example, if a device in the figures is inverted, elements described as “under” or “beneath” other elements or features would then be oriented “over” the other elements or features.

[0091] From the above description of the invention, those skilled in the art will perceive improvements, changes and modifications. Such improvements, changes and modifications within the skill of the art are intended to be covered by the appended claims. All references, publications, and patents cited in the present application are herein incorporated by reference in their entirety.