Field of the Invention

The present invention relates to an end actuator mechanism and control algorithm for a decision mechanism that improves object manipulation in robotic production lines used in industry to increase production efficiency and is based on mechatronic, robotic, programming and control basis to be applied to soft, brittle, rigid etc. various objects and allows soft, brittle, rigid etc. various objects to be grasped or moved.

Prior Art

Industrial robots can be defined as machines that do business in the industry by transporting objects such as parts, materials and work tools by means of an end- function connected to the last limb, which repeatedly follows the trajectories taught by programming by means of the rotational and/or sliding joints with a certain number of axes and limbs and the actuators that activate these joints. The reflection of the word robot, which was first used by a playwright named Karel Capek in the beginning of the 20 ^th century, aroused in the literature and later in the world of science, grew day by day, combined with the concept of Artificial Intelligence and pioneered developments in technology. In this way, the science of robotics, which progresses in a controlled manner, continues its development by integrating with many disciplines such as semiconductors, artificial intelligence, power electronics, computer vision, programming, communication, control, mechatronic systems, and materials science. Robot arms, mobile robots, humanoid robots, spider-like robots, medical robots and even robots used for space exploration from past to present are being integrated with new technologies day by day and offered to make life easier for humanity.

Industrial manipulators significantly increase the quality and efficiency in production. They can carry out their operations without getting tired and can work much faster and safer than individuals. They are not affected by negative factors such as loud noises, harmful rays and high temperatures. They can repeat the operations taught previously by means of programming, many times with very high precision. Although the initial setup costs are high, it is a more profitable investment in the long term and has started to be preferred even by medium-sized companies today. Despite all these advantages, the intervention capabilities of the robot manipulator in case of danger are limited by its program and in case of an unexpected situation; it is not possible to react like a human. Besides, although its movements are much more sensitive and reproducible than humans, the operating space is limited with its limbs and joints. Industrial robots work dependent on user programming and required to be reprogrammed to be used for a different aim.

Today, robots are used in assembly and disassembly processes, such as handlingarranging, turning-rotating, mixing, welding, painting, cutting, drilling, sharpening, polishing and deburring in large production facilities.

The motion principles of the robots are based on placing the trajectory to be followed by the end actuator into the absolute coordinate system by means of transformation matrices and converting these coordinates into joint slip and/or rotation amounts with the help of kinematic calculations and transmitting them to the actuators. The trajectory to be processed in industrial robots is determined by online and offline programming methods. Online programming is performed by means of the control panel (teach pendant) connected to the robot and the trajectory to be followed by the robot is shown to the robot with the buttons and control structures, the determined points are recorded and thus introduced to the robot. These points introduced to the robot are translated into commands in the robot programming language. On the other hand, offline programming is software programming by coding through a programming language supported by the robot. Today, it is also possible to make coding on the touch panel in most of current robot control panels. On the other hand, robot and the workspace can be simulated in three dimensions and the determination of the trajectory can thus be performed offline by means of the graphic-based programs prepared by industrial robot manufacturers and offered to users alongside robots. Trajectory determination process can also be performed by converting the image data taken from the camera into coordinates by subjecting it to image processing techniques such as filtering and edge detection algorithms as a result of technological developments in the field of computer vision in recent years in addition to all these methods.

In the state of the art, many of the gripper mechanisms used in the literature and industry are based on control methods performed through the manipulation of hard objects. At this phase, it only contains applications where most of the object interaction is on/off through the control of the finger positions. In addition, there are applications where a force sensor is placed on finger mechanisms or a contact sensor is used. The positions of the fingers are performed as on/off according to the result of the sensor interaction in applications where contact sensors are used. The common problem of these applications is that they are insufficient for the variety of physical properties of the manipulated object, such as hardness and size. Meanwhile applications using only position control are insufficient in terms of manipulation of various objects, when the force reference to be applied cannot be determined, the object may slip between the fingers. Applications that use only user-defined force control in errors such as slipping etc.are also insufficient.

The end actuator mechanism must be able to operate effectively with the objects it interacts with so as to enable the same performing different tasks. Many of the designs in the literature are based on solid bodies (non-deformed rigid bodies). This causes interactions that will damage the objects in the interaction of more sensitive materials/objects. Solutions in which precision force sensors with multiple degrees of freedom are used and this information is interpreted and controlled with software, which have a high probability of error, expensive and unsatisfactory results are emphasized for this problem. Furthermore, even these solution methods may cause security weakness in terms of human-robot interaction studies within the scope of Industry 4.0. It is not sufficient to artificially provide the precision of the mechanism designed for this purpose to the environment. Besides, It is possible to cause errors such as damage to the object, etc. in case of slippage or insufficient grip during the manipulation of objects. No control algorithms are available in which both adaptive force control and position control are performed, and except those, taking into account the physical properties of the object such as surface smoothness.

The inventive decision and control algorithm provides manipulation of any object whose hardness, dimensions and surface roughness are unknown without slipping and damage by using a hybrid adaptive force and position-control. Decision and control algorithm and force sensors are used sequentially so as to obtain information regarding whether slipping occurs or not and grip information during object manipulation. It ensures to update the force reference determined by the user and initially applied so that the minimum required force value is obtained without slipping and damaging the object by processing the information obtained from the position and the force sensors on the mechanism. The dimensions of the object can be obtained with the help of the position sensor in the decision and control algorithm. The contact force value can be obtained during the object interaction with the force sensors in the decision and control algorithm of the invention subject to application. Safer object interaction is provided by designing a hybrid force-position controller based anti-slip adaptive force-decision mechanism with the inventive decision and control algorithm. In addition, it is possible to effectively manipulate objects of different hardness/sensitivity. While the algorithm in the invention, which is the subject of the application, performs these, it gives priority to the force controller during the interaction of sensitive objects, and to the position controller for the grip/holding phase, and allows the algorithm to change the reference value determined by the data collected from the force sensors. The invention, which is the subject of the application, plays an important role in terms of object-robot interaction so as to increase production efficiency within the scope of Industry 4.0 This makes it possible to safely manipulate different types of objects (metal, plastic, paper, food, etc.).

In the state of the art, there is no explanation regarding the technical features and the technical effects provided by the invention of the present application. In the current application, there is no such a control algorithm for the decision mechanism that improves object manipulation in robotic production lines used in industry to increase production efficiency and is based on mechatronic, robotic, programming and control basis to be applied to soft, brittle, rigid etc. various objects and which allows soft, brittle, rigid etc. various objects to be transported or moved.

Objects of the Invention

The aim of the present invention is to provide a decision mechanism and control algorithm that enables the manipulation of any object, without slipping and damage, whose hardness, dimensions and surface roughness are unknown by using adaptive force and position control in a hybrid way.

Another aim of the invention is to provide a decision and control algorithm in which force sensors are used sequentially so as to obtain information regarding whether slipping occurs or not and grip information during object manipulation.

Another aim of the invention is to provide a decision mechanism and control algorithm that ensures to update the force reference determined by the user and initially applied so that the minimum required force value is obtained without slipping and damaging the object by processing the information obtained from the position of the force sensors on the finger.

Another aim of the invention is to provide a decision mechanism and control algorithm that ensures receiving information about the position of the fingers and the dimensions of the object with the help of the position sensors.

Another aim of the invention is to provide a decision mechanism and control algorithm in which contact force value can be obtained during the object interaction with the force sensors.

Another aim of the invention is to obtain a decision mechanism and control algorithm in which safer object interaction is provided by designing a hybrid forceposition controller based anti-slip adaptive force-decision mechanism. Another aim of the invention is to provide a decision mechanism and control algorithm that makes it possible to effectively manipulate objects of different hardness/sensitivity.

Another aim of the invention is to provide a decision mechanism and control algorithm that gives priority to the force controller during the interaction of sensitive objects and to the position controller for the grip/holding phase and allows changing the reference value determined by the user with the help of the data collected from the force sensors.

Another aim of the invention is to develop a decision mechanism and control algorithm that plays an important role in terms of object-robot interaction so as to increase production efficiency within the scope of Industry 4.0

Brief Description of the Invention

In the control algorithm for a decision mechanism defined in the first claim and other claims dependent on this claim, realized to achieve the aim of the present invention, first of all the user sends a position reference signal to the fingers with the microprocessor using serial communication in the hybrid force-position control based anti-slip control mechanism for object manipulation. A force reference signal of the interaction between the fingers and the object is sent with the microprocessor by the user using serial communication. Objects are grasped by comparing the force information obtained from the fingers with the previous information as vector. The decision mechanism controls the automatic change of the force reference by calculating the information about the grasping, manipulation and sliding of the objects. The command signal required to activate the motors and calculated from the position and force error of the fingers is obtained. This obtained signal is sent to the motor drivers by means of connectors via the microprocessor. The position control signal is generated mathematically as a result of the error calculation between the position reference and the current position of the fingers. A force control signal is generated by means of the designed force controller of the error value calculated by the signal generated at the output of the decision mechanism and the signals obtained from the force sensors placed on the fingers. Command signal is obtained which is required to drive the engine by mathematically summing the generated position and force control signals. A signal is generated that shows the current location of the fingers, which is obtained from the position sensors on the fingers and used for comparison with the position reference. Vectorial signal value is obtained from force sensors placed sequentially on the fingers. The signal obtained from the force sensors is finally transmitted to the decision mechanism. Thus, soft, brittle, rigid, etc. various objects can be transported or moved by preventing slip.

Detailed Description of the Invention

The end actuator decision mechanism and control algorithm realized to achieve the aim of this invention are shown in the attached figures, in which;

Figure 1 . Is a perspective view of the end actuator mechanism.

Figure 2. Is a schematic view of the control mechanism.

Figure 3. It is the flowchart view of the decision algorithm.

The parts in the figure are enumerated one by one and the parts correspond to these numbers are given in the following.

1 . End actuator mechanism.

2. Decision mechanism

3. Fingers

4. Force Sensor

5. Position sensor

6. First support part

7. Second support part

8. First drive part

9. Second drive part

10. Mechanism connecting piece

11 . Threaded connecting piece

12. Upper body connection plate

13. First thread 14. Third support part

15. Second thread

16. Motor

17. Lower body plate

18. Control mechanism

18.1. Position reference

18.2. Force reference

18.3. Hybrid force-position controller block

18.4. Position controller

18.5. Force controller

18.6. Position control signal

18.7. Force control signal

18.8. Position value

18.9. Force value

18.10. Decision signal

100. Control algorithm for end actuator decision mechanism

An end actuator mechanism (1 ) that improves object manipulation in robotic production lines used in industry to increase production efficiency and is based on mechatronic, robotic, programming and control basis to be applied to soft, brittle, rigid etc. various objects and allows soft, brittle, rigid etc. various objects to be transported or moved, mainly comprises the following;

- at least one decision mechanism (2) operating according to the decision algorithm (100),

- fingers (3) that is based on mechatronics, robotics, programming and control that can be applied to objects and allow soft, brittle, rigid etc. various objects to be transported or moved,

- position sensor (5) that enables the position detection of the fingers (3) while moving, force sensor (4), which detects the force that the fingers (3) will exert while moving the objects,

- end actuator mechanism (1 ) consisting of first support part (6), second support part (7), first drive part (8), second drive part (9), mechanism connecting piece (10), threaded connecting piece (11 ), upper body connection plate (12), first thread (13), third support part (14), second thread (15), engine (16) and lower body plate (17),

- a control mechanism (18) that improves object manipulation of fingers (3) and is based on mechatronic, robotic, programming and control basis to be applied to soft, brittle, rigid etc. various objects and enables the control of soft, brittle, rigid etc. various objects while being transported or moved.

The inventive end actuator mechanism (1 ) improves object manipulation in robotic production lines used in industry to increase production efficiency and is based on mechatronic, robotic, programming and control basis to be applied to soft, brittle, rigid etc. various objects and enables the control of soft, brittle, rigid etc. various objects while being transported or moved.

The end actuator mechanism (1 ) and the decision algorithm (100), which are included in an application of the invention provides manipulation of any object whose hardness, dimensions and surface roughness are unknown without slipping and damage by using a hybrid adaptive force and position-control. End actuator mechanism (1 ) and decision algorithm (100) provides that forces sensors (4) are used sequentially so as to obtain information regarding whether slipping occurs or not and grip information during object manipulation. End actuator mechanism (1 ) and decision algorithm (100) ensures to update the force reference (18.2) determined by the user and initially applied so that the minimum required force value is obtained without slipping and damaging the object by processing the information obtained from the position and the force sensors (4) on the finger (3). End actuator mechanism (1 ) and decision algorithm (100) provides information about the position of the fingers (3) and the dimensions of the object can be obtained with the help of the position sensor. End actuator mechanism (1 ) and decision algorithm (100) provides to obtain the contact force value during the interaction of the object with the force sensors (4). End actuator mechanism (1 ) and decision algorithm (100) provides safer object interaction by designing a hybrid force-position controller based anti-slip adaptive force-decision mechanism. End actuator mechanism (1 ) and decision algorithm (100) makes it possible to effectively manipulate objects of different hardness/sensitivity. End actuator mechanism (1 ) and decision algorithm (100) gives priority to the force controller during the interaction of sensitive objects, and to the position controller for the grip/holding phase, and allows the user to change the reference value determined by the data collected from the force sensors. End actuator mechanism (1 ) and decision algorithm (100) play an important role in terms of object-robot interaction so as to increase production efficiency within the scope of Industry 4.0.

Control algorithm (100) for the decision mechanism (2) that improves object manipulation in robotic production lines used in industry to increase production efficiency and is based on mechatronic, robotic, programming and control basis to be applied to soft, brittle, rigid etc. various objects and which allows soft, brittle, rigid etc. various objects to be transported or moved according to claim 1 , characterized in that; it mainly comprises the following process steps;

- sending position reference (18.1 ) signal with microprocessor by user to fingers (3) using serial communication in hybrid force-position control based anti-slip control mechanism (1 ) for object manipulation (101 ),

- sending a force reference signal (18.2) of the interaction between the fingers (3) and the object with the microprocessor by the user using serial communication (102),

- grasping objects by comparing the force information obtained from the fingers (3) with the previous information as vector (103), controlling the decision mechanism (2) where the force reference (18.2) is automatically changed by calculating the information about the grasping, manipulation and sliding of objects (104),

- obtaining the command signal required to activate the motors (16) and calculated from the position and force error of the fingers (3) (105),

- sending this obtained signal to the motor (16) driver by the micro processor via connectors (106),

- mathematically generating a position control signal (18.6) as a result of the error calculation between the position reference (18.1 ) and the current location (18.8) of the fingers (3) (107),

- generating a force control signal (18.10) by means of the designed force controller (18.5) of the error value calculated with the signal generated at the output of the decision mechanism (2) and the signal (18.7) obtained from the force sensors (4) placed on the fingers (3) (108),

- obtaining the command signal required to drive the motor (16) by mathematically summing the generated position (18.6) and force control signals (18.7) (109),

- generating the signal obtained from the position sensors (5) on the fingers (3) and indicating the current position of the fingers (3) used for comparison with the position reference (18.1 ) (110),

- obtaining vectorial signal value from force sensors (4) placed sequentially on the fingers (3) (1 11 ),

- transmitting the signal obtained from the force sensors (4) to the decision mechanism (2) (112).

The usage of the control algorithm (100) for decision mechanism (2) included in one embodiment of the invention is realized as follows. First of all the user sends a position reference (18.1 ) signal to the fingers (3) with the microprocessor using serial communication in the hybrid force-position control based anti-slip control mechanism (18) for object manipulation in the control algorithm (100) for the decision mechanism (2) (101 ). A force reference signal (18.2) of the interaction between the fingers (3) and the object is sent with the microprocessor by the user using serial communication after the process step of 101 (102), objects are grasped by comparing the force information obtained from the fingers (4) with the previous information as vector after the force reference (18.2) is sent (102) (103). The decision mechanism (2) is controlled where the force reference (18.2) is automatically changed by calculating the information about the grasping, manipulation and sliding of objects after the objects are grasped (103) (104). Command signal required to activate the motor (16) and calculated from the position and force error of the fingers (3) is obtained after the process step of 104 (105). This signal obtained in the process step of 105 is sent to the motor (16) driver by the microprocessor via connectors (107). A position control signal (18.6) is generated mathematically as a result of the error calculation between the position reference (18.1 ) and the current position of the fingers (3) after the signals are sent (107) (108), A force control signal (18.7) is generated by means of the designed force controller (18.5) of the error value calculated by the signal generated at the output of the decision mechanism (2) and the signals obtained from the force sensors (4) placed on the fingers (3) (109). Command signal is obtained which is required to drive the motor (16) by mathematically summing the generated position (18.6) and force control signals (18.7) (1 10). The signal obtained from the position sensor (5) located in the motor (16) or the end actuator mechanism (1 ) and indicating the current position of the fingers (3) used for comparison with the position reference (18.1 ) is generated (11 1 ). Vectorial signal value is obtained from force sensors (4) placed sequentially on the fingers (3). The signal obtained from the force sensors (4) is finally transmitted to the decision mechanism (2) (1 12). Thus, soft, brittle, rigid, etc. various objects can be transported or moved by preventing slip.