Control of Swarming Robots

• US 20170072565A1
• Filed: 05/05/2015
• Published: 03/16/2017
• Est. Priority Date: 05/05/2014
• Status: Active Grant

• Current Assignee: Georgia Tech Research Corporation (University System of Georgia)
• Original Assignee: Georgia Tech Research Corporation (University System of Georgia)
• Inventors: Lee, Sung Gun, Diaz-Mercado, Yancy, Chopra, Smriti, Egerstedt, Magnus
• Granted Patent: US 10,537,996 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B25J 9/1682 Dual arm manipulator; Coordination of several manipulators
• CPC Class Codes: G05B 2219/39153 Human supervisory control of swarm
• CPC Class Codes: G05D 1/0016 characterised by the operator's input device input arrangements for computing systems in general G06F3/00
• CPC Class Codes: G05D 1/0027 involving a plurality of vehicles, e.g. fleet or convoy travelling fleet control of land vehicles from a control room G05D1/0297; traffic control systems for road vehicles G08G1/00; for marine craft G08G3/00; for aircraft G08G5/00

Abstract

Systems and methods for controlling a swarm of mobile robots are disclosed. In one aspect, the robots cover a domain main of interest. Each robot receives a density function indicative of at least one area of importance in the domain of interest, and calculates a velocity vector based on the density function and a displace vector relative to an adjacent robot. Each robot moves to the area of importance according to its velocity vector. In some aspects, the robots together perform a sequence of formations. Each robot mimics a trajectory as part of its performance by switching among a plurality of motion modes. Each robot determines its next motion mode based on a displacement vector relative to an adjacent robot.

Claims

1. A multi-robot system comprising a plurality of mobile robots, each robot including:

a sensor for detecting relative distance and angle measurements of an adjacent robot; and

a processor, coupled to the sensor, the processor configured to;

receive, from the sensor, data representative of the relative distance and angle measurements of the adjacent robot; and

determine a displacement vector relative to the adjacent robot based on the relative distance and angle measurements detected by the sensor.

2. The system of claim 1, wherein the system is for covering a domain of interest:

wherein the plurality of mobile robots together cover the domain of interest;

wherein each robot further comprises a memory storing data representative of the domain of interest; and

wherein the processor is further configured to;

receive data representative of a density function indicative of at least one area of importance in the domain of interest;

calculate a velocity vector based on the density function and the displacement vector relative to the adjacent robot; and

output for moving the robot to the at least one area of importance in the domain of interest based on the velocity vector.

3. The system of claim 2, wherein the domain of interest is divided based on the Voronoi cell partition, and each robot occupies a Voronoi cell.

4. The system of claim 3, wherein the processor is further configured to compute a change in the robot'"'"'s Voronoi cell, and a change in the adjacent robot'"'"'s Voronoi cell.

5. The system of claim 4, wherein the processor is further configured to calculate the velocity vector to compensate for the changes.

6. The system of claim 2, wherein the processor is further configured to receive the data representative of the density function from a computing device.

7. The system of claim 6, wherein the computing device has a touchable screen, outputs the density function in response to a touch on the screen, and determines the density function based on a position and amount of the touch on the screen.

8. A method for controlling the multi-robot system of claim 1 comprising:

receiving, by the processor on each robot, from the sensor, the data representative of the relative distance and angle measurements of an adjacent robot;

determine, by the processor, the displacement vector relative to the adjacent robot based on the relative distance and angle measurements detected by the sensor;

receiving data representative of a density function indicative of at least one area of importance in a domain of interest;

calculating a velocity vector based on the density function and the displacement vector relative to the adjacent robot; and

outputting for moving the robot to the at least one area of importance in the domain of interest based on the velocity vector;

wherein the plurality of mobile robots cover the domain of interest.

9. The method of claim 8, wherein calculating the velocity vector based on the density function comprises calculating the velocity vector based on a time-varying density function.

10. The method of claim 8, wherein receiving the data representative of the density function comprises receiving the data representative of the density function from a computing device having a touch screen, and wherein the density function is determined based on a position and amount of the touch on the screen.

11. The system of claim 1, wherein the system is for performing a sequence of formations;

wherein the plurality of mobile robots together perform the sequence of formations, each robot mimicking a trajectory as part of its performance mimicking the trajectory by switching among a plurality of motion modes; and

wherein the processor further configured to;

receive data representative of the sequence of formations;

determine a scaling factor for the robot'"'"'s next mode based on the displacement vector;

determine a rotation factor for the robot'"'"'s next mode based on the displacement vector;

determine a switch time for the robot'"'"'s next mode based on the displacement; and

output for executing the next mode based on the scaling factor, the rotation factor and the switch time.

12. The system of claim 11, wherein the processor is further configured to optimize the scaling factor, rotation factor and switch time based on an optimality condition and a costate equation.

13. The system of claim 11, wherein the processor is further configured to optimize the scaling factor, rotation factor and switch time by performing a steepest decent algorithm.

14. The system of claim 11, wherein the scaling factor scales the displacement vector by multiplying a relative distance measurement between two adjacent robots by a constant.

15. The system of claim 11, wherein the rotating factor rotates the displacement vector by adding a constant to a relative angle measurement.

16. A method for controlling the multi-robot system of claim 11 comprising:

receiving, by the processor on each robot, data representative of the sequence of formations;

receiving, by the processor, from the sensor, data representative of relative distance and angle measurements between the robot and its adjacent robot;

determining, by the processor, the displacement vector relative to the adjacent robot based on the relative distance and angle measurements;

determining the scaling factor for the robot'"'"'s next mode based on the displacement vector;

determining the rotation factor for the robot'"'"'s next mode based on the displacement vector;

determining the switch time for the robot'"'"'s next mode based on the displacement; and

outputting for executing the next mode based on the scaling factor, the rotation factor and the switch time;

wherein the plurality of robots perform the sequence of formations in a decentralizing manner.

17. The method of claim 16 further comprising optimizing the scaling factor, rotation factor and switch time based on an optimality condition and a costate equation.

18. The method of claim 16 further comprising optimizing the scaling factor, rotation factor and switch time by performing a steepest decent algorithm.

19. The method of claim 16 further comprising scaling with the scaling factor the displacement vector by multiplying a relative distance measurement between two adjacent robots by a constant.

20. The method of claim 16 further comprising rotating with the rotating factor the displacement vector by adding a constant to a relative angle measurement.

21. The system of claim 2, wherein the processor is further configured to compute the velocity vector based on a time-varying density function.