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Title:
SYSTEM FOR CONTROLLING AT LEAST ONE INDUSTRIAL OBJECT HAVING AN ARRANGEMENT RESPONSIVE TO A STIMULUS AND METHOD OF IMPLEMENTING THE SAME
Document Type and Number:
WIPO Patent Application WO/2023/209701
Kind Code:
A1
Abstract:
A system for controlling at least one industrial object having an arrangement responsive to a stimulus comprises: at least one unmanned aerial vehicle with an actuator configured for producing the stimulus and sensing means; and a control unit further comprising: a processor being in communication with the unmanned aerial vehicle, and a memory connected to th processor and storing instructions. The instructions include locating an industrial object by the sensing means, sensing data relating to a state of the industrial object, interrogating sensed data via a communication unit, analyzing sensed data the processor, making decisions if applying the stimulus to the arrangement is required by the processor, flying the unmanned aerial vehicle to the industrial object, if required and applying the stimulus such that the arrangement provides a predetermined response to the stimulus.

Inventors:
ULMER JOSHUA (IL)
Application Number:
PCT/IL2023/050411
Publication Date:
November 02, 2023
Filing Date:
April 23, 2023
Export Citation:
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Assignee:
EMI INTEGRATED SYSTEMS LTD (IL)
International Classes:
B64C39/02; G05G15/00; B64U101/00
Foreign References:
KR20180110559A2018-10-10
US20210356237A12021-11-18
Attorney, Agent or Firm:
BRESSLER, Eyal et al. (IL)
Download PDF:
Claims:
Claims:

1. A system for controlling at least one industrial object having an arrangement responsive to a stimulus; said system comprising: a. at least one unmanned aerial vehicle further comprising: i. an actuator configured for producing said stimulus; ii. sensing means; b. a control unit further comprising: i. a processor being in communication with said unmanned aerial vehicle; ii. a memory connected to said processor and storing instructions which when executed by said processor cause:

1. locating said at least one industrial object by said sensing means of said at least one unmanned aerial vehicle;

2. sensing data relating to a state of said at least one industrial object by sensing means of said at least one unmanned aerial vehicle;

3. interrogating sensed data via said first and second communication units;

4. analyzing sensed data by said processor;

5. making decisions if applying said stimulus to said arrangement is required by said processor;

6. flying said at least one unmanned aerial vehicle to said at least one industrial object, if required;

7. applying said stimulus such that said arrangement provides a predetermined response to said stimulus.

2. The system according to claim 1 , wherein at least one of said processor and said memory is based in a location selected from the group consisting of said unmanned aerial vehicle, a cloud-based software means, a base station and any combination thereof.

3. The system according to claim 1, wherein said sensing means is selected from the group consisting of an imaging sensor, a light sensor, a color sensor, a radar, an acoustic sensor, a temperature sensor, a humidity sensor, a near- field sensor, an radio-frequency sensor, a BlueTooth sensor and any combination thereof. The system according to claim 1 , wherein said unmanned aerial vehicle and said control unit are connected to each other by a communication channel selected from the group consisting of a BlueTooth communication, a Wi-Fi communication, a radio-frequency communication, a broadband internet communication, an optical communication and any combination thereof. The system according to claim 3, wherein said light sensor is sensitive to spectral band selected from the group consisting of an ultraviolet band, a visual band, an infrared band and any combination thereof. The system according to claim 1, wherein said instructions of analyzing sensed data and making decisions are implemented by means of an algorithm selected from the group consisting of artificial intelligence, machine learning, supervised learning, reinforcement learning, deep learning and any combination thereof. The system according to claim 1, wherein said arrangement is responsive to said stimulus selected from the group consisting of a mechanical stimulus, an electromagnetic stimulus, optical stimulus, an acoustic stimulus and any combination thereof. The system according to claim 7, wherein said electromagnetic stimulus is performed by said actuator selected from the group consisting of a radio frequency device, a near-field communication device, a Bluetooth device and any combination thereof. The system according to claim 1, wherein said control unit is in communication with said at least one industrial object; said base station is configured for interrogating operational parameters of said at least one industrial object by said processor. The system according to claim 1 comprising stationary sensing means selected from the group consisting of an imaging sensor, a light sensor, a color sensor, a radar, an acoustic sensor, a temperature sensor, a humidity sensor, a near-field sensor, an radio-frequency sensor, a BlueTooth sensor and any combination thereof; said stationary sensing means is in communication with said base station and interrogatable by said processor. The system according to claim 1, wherein said at least one industrial object is provided with anchoring pads for landing said at least one unmanned aerial vehicle. A method of controlling at least one industrial object having an arrangement responsive to a stimulus; said method comprising steps of: a. providing a system for controlling at least one industrial object having an arrangement responsive to a stimulus: said system comprising: i. at least one unmanned aerial vehicle further comprising:

1. an actuator configured for producing said stimulus;

2. sensing means; ii. a control unit further comprising:

1. a processor being in communication with said unmanned aerial vehicle;

2. a memory connected to said processor and storing instructions for said processor; b. locating said at least one industrial object by said sensing means of said at least one unmanned aerial vehicle; c. sensing data relating to a state of said at least one industrial object by sensing means of said at least one unmanned aerial vehicle; d. interrogating sensed data via said first and second communication units; e. analyzing sensed data by said processor; f. making decisions if applying said stimulus to said arrangement is required by said processor; g. flying said at least one unmanned aerial vehicle to said at least one industrial object, if required; h. applying said stimulus such that said arrangement provides a predetermined response to said stimulus. The method according to claim 12, wherein at least one of said processor and said memory is based in a location selected from the group consisting of said unmanned aerial vehicle, a cloud-based software means, a base station and any combination thereof The method according to claim 12, wherein said step of sensing data relating to a state of said at least one industrial object is performed by said sensing means selected from the group consisting of an imaging sensor, a light sensor, a color sensor, a radar, an acoustic sensor, a temperature sensor, a humidity sensor, a near-field sensor, an radio-frequency sensor, a BlueTooth sensor and any combination thereof. The method according to claim 12, wherein said unmanned aerial vehicle and said control unit are connected to each other by a communication channel selected from the group consisting of a BlueTooth communication, a Wi-Fi communication, a radio-frequency communication, a broadband internet communication, an optical communication and any combination thereof. The method according to claim 13, wherein said light sensor is sensitive to spectral band selected from the group consisting of an ultraviolet band, a visual band, an infrared band and any combination thereof. The method according to claim 8, wherein said steps of analyzing sensed data and making decisions are implemented by means of an algorithm selected from the group consisting of artificial intelligence, machine learning, supervised learning, reinforcement learning, deep learning and any combination thereof. The method according to claim 8, wherein stimulus generated by said actuator is selected from the group consisting of a mechanical stimulus, an electromagnetic stimulus, optical stimulus, an acoustic stimulus and any combination thereof. The system according to claim 18, wherein said electromagnetic stimulus is performed by said actuator selected from the group consisting of a radio frequency device, a near-field communication device, a Bluetooth device and any combination thereof. The method according to claim 8 comprising steps of establishing communication between said control unit and said at least one industrial object and interrogating operational parameters of said at least one industrial object by said processor. The method according to claim 8 comprising steps of providing stationary sensing means selected from the group consisting of an imaging sensor, a light sensor, a color sensor, a radar, an acoustic sensor, a temperature sensor, a humidity sensor , a near-field sensor, an radio-frequency sensor, a BlueTooth sensor and any combination thereof, establishing communication between said base station and said stationary sensing means and interrogating data sensed by said providing stationary sensing means by said processor. The method according to claim 8 wherein said step of applying said stimulus comprises landing said at least one unmanned aerial vehicle on anchoring pads on said industrial object. A method of training a system for controlling at least one industrial object having an arrangement responsive to a stimulus; said method comprising steps of: a. providing said system for controlling at least one industrial object having an arrangement responsive to a stimulus; said system comprising: i. at least one unmanned aerial vehicle further comprising:

1. an actuator configured for producing said stimulus;

2. sensing means; ii. a control unit further comprising:

1. a processor being in communication with said unmanned aerial vehicle;

2. a memory connected to said processor and storing instructions for said processor; b. performing supervised learning of said system by: i. modelling an operation procedure within an operation environment of interest; ii. positioning said at least one unmanned aerial vehicle in operation points of interest; iii. sensing said operation environment of interest by said sensing means of said at least one unmanned aerial vehicle; iv. generating instructions relating to positioning said at least one unmanned aerial vehicle in said operation points of interest; v. storing generated instruction is said memory. The method according to claim 23, wherein at least one of said processor and said memory is based in a location selected from the group consisting of said unmanned aerial vehicle, a cloud-based software means, a base station and any combination thereof. The method according to claim 23, wherein said step of performing supervised learning comprises adjusting positions of said operation points of interest and a flying path. The method according to claim 23, wherein said step of adjusting positions of said operation points of interest and a flying path comprises manually set reference flying points through which said unmanned aerial vehicle flies. The method according to claim 26, wherein setting said reference flying points are set by a command manually activated when said unmanned aerial vehicle is positioned in said reference flying points. The method according to claim 23, wherein said step of performing supervised learning comprises user-supervised flying said unmanned aerial vehicle and storing instructions relating to said user-supervised flying. The method according to claim 23, wherein said step of positioning said at least one unmanned aerial vehicle in operation points of interest comprises manually placing said unmanned aerial vehicle into said operation points of interest and storing instructions relating to said operation points of interest. The method according to claim 23, wherein said step of sensing data relating to a state of said at least one industrial object is performed by said sensing means selected from the group consisting of an imaging sensor, a light sensor, a color sensor, a radar, an acoustic sensor, a temperature sensor, a humidity sensor, a near-field sensor, an radio-frequency sensor, a BlueTooth sensor and any combination thereof. The method according to claim 23, wherein said unmanned aerial vehicle and said control unit are connected to each other by a communication channel selected from the group consisting of a BlueTooth communication, a Wi-Fi communication, a radio-frequency communication, a broadband internet communication, an optical communication and any combination thereof. The method according to claim 31, wherein said light sensor is sensitive to spectral band selected from the group consisting of an ultraviolet band, a visual band, an infrared band and any combination thereof. The method according to claim 23, wherein said steps of analyzing sensed data and making decisions are implemented by means of an algorithm selected from the group consisting of artificial intelligence, machine learning, supervised learning, reinforcement learning, deep learning and any combination thereof. The method according to claim 23, wherein stimulus generated by said actuator is selected from the group consisting of a mechanical stimulus, an electromagnetic stimulus, optical stimulus, an acoustic stimulus and any combination thereof. The system according to claim 34, wherein said electromagnetic stimulus is performed by said actuator selected from the group consisting of a radio frequency device, a near-field communication device, a Bluetooth device and any combination thereof. The method according to claim 23 comprising steps of establishing communication between said control unit and said at least one industrial object and interrogating operational parameters of said at least one industrial object by said processor. The method according to claim 23 comprising steps of providing stationary sensing means selected from the group consisting of an imaging sensor, a light sensor, a color sensor, a radar, an acoustic sensor, a temperature sensor, a humidity sensor , a near-field sensor, an radio-frequency sensor, a BlueTooth sensor and any combination thereof, establishing communication between said base station and said stationary sensing means and interrogating data sensed by said providing stationary sensing means by said processor. The method according to claim 23 wherein said step of applying said stimulus comprises landing said at least one unmanned aerial vehicle on anchoring pads on said industrial object.

Description:
SYSTEM FOR CONTROLLING AT LEAST ONE INDUSTRIAL OBJECT HAVING AN

ARRANGEMENT RESPONSIVE TO A STIMULUS AND METHOD OF

IMPLEMENTING THE SAME

FIELD OF THE INVENTION

The present invention generally pertains to robotic systems and, more particularly, to systems for controlling industrial objects by airborne actuators.

BACKGROUND OF THE INVENTION

There are many applications in different fields in the world that require mechanical and / or near field touchless actuation and/or a near presence of a human operator in order to operate. In many of these applications, remote control can be implemented via wireless or cable communication, but applying a mechanical or electromagnetic near-field stimulus can be in certain cases more reliable and simpler implementable. Use of direct actuating of the industrial objects can result in cost reduction. Thus, there is a long-felt and unmet need for providing an actuator able to control an industrial object by applying a mechanical or electromagnetic stimulus.

SUMMARY OF THE INVENTION

It is hence one object of the invention to disclose a system for controlling at least one industrial object having an arrangement responsive to a stimulus. The aforesaid system comprises: (a) at least one unmanned aerial vehicle further comprising: (i) an actuator configured for producing said stimulus; (ii) sensing means; (b) a control unit further comprising: (i) a processor being in communication with said unmanned aerial vehicle; (ii) a memory connected to said processor and storing instructions which when executed by said processor cause: (1) locating said at least one industrial object by said sensing means of said at least one unmanned aerial vehicle; (2) sensing data relating to a state of said at least one industrial object by sensing means of said at least one unmanned aerial vehicle; (3) interrogating sensed data via said first and second communication units; (4) analyzing sensed data by said processor; (5) making decisions if applying said stimulus to said arrangement is required by said processor; (6) flying said at least one unmanned aerial vehicle to said at least one industrial object, if required; (7) applying said stimulus such that said arrangement provides a predetermined response to said stimulus.

Another object of the invention is to disclose the at least one of said processor and said memory based in a location selected from the group consisting of said unmanned aerial vehicle, a cloudbased software means, a base station and any combination thereof.

A further object of the invention is to disclose the sensing means selected from the group consisting of an imaging sensor, a light sensor, a color sensor, a radar, an acoustic sensor, a temperature sensor, a humidity sensor, a near-field sensor, an radio-frequency sensor, a BlueTooth sensor and any combination thereof. A further object of the invention is to disclose at least one unmanned aerial vehicle and said control unit are connected to each other by a communication channel selected from the group consisting of a BlueTooth communication, a Wi-Fi communication, a radio-frequency communication, a broadband internet communication, an optical communication and any combination thereof.

A further object of the invention is to disclose the light sensor sensitive to spectral band selected from the group consisting of an ultraviolet band, a visual band, an infrared band and any combination thereof.

A further object of the invention is to disclose the instructions of analyzing sensed data and making decisions implemented by means of an algorithm selected from the group consisting of artificial intelligence, machine learning, supervised learning, reinforcement learning, deep learning and any combination thereof.

A further object of the invention is to disclose the arrangement responsive to said stimulus selected from the group consisting of a mechanical stimulus, an electromagnetic stimulus, optical stimulus, an acoustic stimulus and any combination thereof.

A further object of the invention is to disclose the electromagnetic stimulus performed by said actuator selected from the group consisting of a radio frequency device, a near-field communication device, a Bluetooth device and any combination thereof.

A further object of the invention is to disclose the control unit which is in communication with said at least one industrial object; said base station is configured for interrogating operational parameters of said at least one industrial object by said processor. A further object of the invention is to disclose the system comprising stationary sensing means selected from the group consisting of an imaging sensor, a light sensor, a color sensor, a radar, an acoustic sensor, a temperature sensor, a humidity sensor, a near- field sensor, an radio-frequency sensor, a BlueTooth sensor and any combination thereof; said stationary sensing means is in communication with said base station and interrogatable by said processor.

A further object of the invention is to disclose the at least one industrial object provided with anchoring pads for landing said at least one unmanned aerial vehicle.

A further object of the invention is to disclose a method of controlling at least one industrial object having an arrangement responsive to a stimulus. The aforesaid said method comprising steps of: (a) providing a system for controlling at least one industrial object having an arrangement responsive to a stimulus: said system comprising: (i) at least one unmanned aerial vehicle further comprising: (1) an actuator configured for producing said stimulus; (2) sensing means; (ii) a control unit further comprising: (1) a processor being in communication with said unmanned aerial vehicle; (2) a memory connected to said processor and storing instructions for said processor; (b) locating said at least one industrial object by said sensing means of said at least one unmanned aerial vehicle; (c) sensing data relating to a state of said at least one industrial object by sensing means of said at least one unmanned aerial vehicle; (d) interrogating sensed data via said first and second communication units; (e) analyzing sensed data by said processor; (f) making decisions if applying said stimulus to said arrangement is required by said processor; (g) flying said at least one unmanned aerial vehicle to said at least one industrial object, if required; (h) applying said stimulus such that said arrangement provides a predetermined response to said stimulus.

A further object of the invention is to disclose a method of training a system for controlling at least one industrial object having an arrangement responsive to a stimulus. The aforesaid method comprises steps of: (a) providing said system for controlling at least one industrial object having an arrangement responsive to a stimulus; said system comprising: (i) at least one unmanned aerial vehicle further comprising: (1) an actuator configured for producing said stimulus; (2) sensing means; (ii) a control unit further comprising: (1) a processor being in communication with said unmanned aerial vehicle; (2) a memory connected to said processor and storing instructions for said processor; (b) performing supervised learning of said system by: (i) modelling an operation procedure within an operation environment of interest; (ii) positioning said at least one unmanned aerial vehicle in operation points of interest; (iii) sensing said operation environment of interest by said sensing means of said at least one unmanned aerial vehicle; (iv) generating instructions relating to positioning said at least one unmanned aerial vehicle in said in operation points of interest; (v) storing generated instruction is said memory.

A further object of the invention is to disclose the step of performing supervised learning comprising user-supervised flying said unmanned aerial vehicle and storing instructions relating to said user-supervised flying.

A further object of the invention is to disclose the step of positioning said at least one unmanned aerial vehicle in operation points of interest comprising manually placing said unmanned aerial vehicle into said operation points of interest and storing instructions relating to said operation points of interest.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to understand the invention and to see how it may be implemented in practice, a plurality of embodiments is adapted to now be described, by way of non-limiting example only, with reference to the accompanying drawings, in which

Fig. 1 is a schematic diagram of a system for controlling at least one industrial object having an arrangement responsive to a stimulus;

Fig. 2 is a schematic diagram of an alternative embodiment of system for controlling at least one industrial object provided with a stationary sensing means;

Fig. 3 is a schematic diagram of an unmanned aerial vehicle;

Fig. 4 is a flowchart of a method of controlling at least one industrial object provided with a stationary sensing means; and

Fig. 5 is a flowchart of a method of training a system for controlling at least one industrial object having an arrangement responsive to a stimulus. DETAILED DESCRIPTION OF THE INVENTION

The following description is provided, so as to enable any person skilled in the art to make use of said invention and sets forth the best modes contemplated by the inventor of carrying out this invention. Various modifications, however, are adapted to remain apparent to those skilled in the art, since the generic principles of the present invention have been defined specifically to provide a system for controlling at least one industrial object having an arrangement responsive to a stimulus and a method of implementing the same.

Reference is now made to Fig. 1 presenting a schematic diagram of system 100 for controlling at least one industrial object. System 100 comprises base station 10, at least one unmanned aerial vehicle (UAV) 20 such as a multicopter. System 100 is configured for controlling a plurality of industrial objects 30. UAV 20 is provided with actuator 25 configured for generating a stimulus applicable for controlling industrial objects 30. Mechanical actuators and touchless actuators such as near-field communication, magnetically and light-operating at visual and infrared spectral bands are in the scope of the present invention. Each object 30 is has arrangement 35 responsive to the stimulus generated by actuator 25. UAV 20 is provided with sensing means 23 constituting an arrangement of sensor such as an imaging sensor, a radar, an acoustic sensor, a temperature sensor, a humidity sensor. UAV 20 carries a first communication unit (not shown). Base station 10 comprises a processor, a memory unit storing instructions for the processor and a second communication unit (not shown) which is in communication with the first communication unit. The instructions stored in the memory unit of base station 10 when executed cause the following. UAV 20 locates industrial object 30 and senses its parameters of interest by sensors 23. The sensed data are interrogated by the processor via the first and second communication units. The processor of base station 10 analyzes the interrogated data and makes decisions of applying the stimulus to industrial object 30 is required. Instructions of analyzing sensed data and making decisions are implemented by means of an algorithm selected from artificial intelligence, machine learning, supervised learning, reinforcement learning, deep learning and like. It should be noted that that the processor and memory unit based in the UAV, base station and cloud-based software means are in the scope of the present invention.

After that, UAV 20 is positioned by processor into proximity of industrial object 30 continuing until landing on industrial object 30. The stimulus is applied by actuator 25 to responsive arrangement 35 of industrial object 30. All of a mechanical stimulus, an electromagnetic stimulus, optical stimulus, an acoustic stimulus are in the scope of the present invention. It should be noted that the parameters of interest relating to industrial objects 30 can be also interrogated by the processor via wire or wireless communication channels.

Reference is now made to Fig. 2, presenting an alternative embodiment of system 100 for controlling at least one industrial object provided with stationary sensing means 40. In addition to sensing means 23 carried by UAV 20, stationary sensing means can include any of the following sensors: an imaging sensor, a radar, an acoustic sensor, a temperature sensor, a humidity sensor.

Reference is now made to Fig. 3 presenting a schematic diagram of UAV 20 landed on industrial object 30. As mentioned above, any actuator 25 such as a mechanical actuator or an electromagnetic (near-field communication, infrared) actuator is in the scope of the invention. Correspondingly, arrangement 35 is responsive to the stimulus generated by actuator 25. Industrial object 30 can be provided with anchoring pads 33 (for example, magnetic anchoring pads) facilitating spot landing of UAV 20.

Reference is now made to Fig. 4 presenting a flowchart of method 180 of controlling at least one industrial object having an arrangement responsive to a stimulus. Method 180 starts with locating the industrial object to be controlled by the sensing means of the UAV (step 110). Then, the parameters relating to the current state of the industrial object are sensed (step 120) and interrogated by the processor (step 130). At step 140, the sensed data analyzed. On the basis of data analysis, decisions relating to need for applying a stimulus to the responsive arrangement are made (step 150). If the stimulus has to be applied. The UAV flies to the industrial object (step 160) and applies the stimulus such that said arrangement provides a predetermined response to said stimulus, for example, opens or closes a predetermined circuit or valve or like (step 170).

Reference is now made to Fig. 5 presenting a flowchart of method 200 of training a system for controlling at least one industrial object having an arrangement responsive to a stimulus. Method 200 starts with modelling an operation procedure within an operation environment of interest (step 210). Then, at least one unmanned aerial vehicle is positioned in points of interest (step 220) and the operation environment (such as point coordinates) is sensed by the sensing means of the unmanned aerial vehicle (step 230). On the basis of the sensed data, the instructions relating to positioning the unmanned aerial vehicle in the operation points of interest are generated. At the end of the method, the generated instructions are stored in the memory of the system (step 250). The positions of the operation points and the flying path can be adjusted in manual or Al manner. The fly pass can include manually set reference flying points through which said unmanned aerial vehicle flies.

The step of setting the reference flying points can be performed by a command manually activated (a button pressable by a user) when said unmanned aerial vehicle is positioned in said reference flying points.

Although the invention has been described in conjunction with specific embodiments thereof, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art. Accordingly, it is intended to embrace all such alternatives, modifications and variations that fall within the spirit and broad scope of the appended claims.




 
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