國立虎尾科技大學 |

Distributed Formation Control in Swarm Robotics.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Distributed Formation Control in Swarm Robotics./
Author:	Wu, Kefan.
Description:	1 online resource (151 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-11, Section: B.
Contained By:	Dissertations Abstracts International85-11B.
Subject:	Digital cameras. -
Online resource:	click for full text (PQDT)
ISBN:	9798382652757

Distributed Formation Control in Swarm Robotics.
Wu, Kefan.

Distributed Formation Control in Swarm Robotics. - 1 online resource (151 pages)

Source: Dissertations Abstracts International, Volume: 85-11, Section: B.

Thesis (Ph.D.)--The University of Manchester (United Kingdom), 2023.

Includes bibliographical references

Inspired by natural swarm collective behaviours such as colonies of bees and schools of fish, coordination strategies in swarm robotics have received significant attention in recent years. Distributed control on formation aims to coordinate a team of robots to form a desired geometric pattern through local information, which is a hot topic in swarm intelligence. The main objective of this thesis is to construct formation algorithms combined with bearing measurements for multi-robot systems and provide applications in real robotic scenarios.First, we establish a basic formation framework based on edge and bearing measurements for networked multi-robot systems. The edge-based and bearing-based protocols are combined in controller design to maximise the advantages of both methods. We discuss the robustness of the mixed controller for both leaderless and leader-follower cases by Lyapunov approach. Simulation case studies are also presented to verify the effectiveness of the theoretical results.Furthermore, a bearing-only collision-free formation coordination strategy is proposed for networked heterogeneous robots, where each robot only measures the relative bearings of its neighbours to achieve cooperation. Different from many existing studies that can only guarantee global asymptotic stability, a gradient-descent control protocol is designed to make the robots achieve a target formation within a given finite time. The stability of the multi-robot system is guaranteed via Lyapunov theory, and the convergence time can be defined by users. The exogenous disturbances in the system and actuator faults in the controller are also considered in convergence analysis. Then, the proposed finite-time bearing-only protocol is extended to linear time-invariant systems. Numerical simulations and lab-based experiments using unmanned ground vehicles are conducted to validate the effectiveness of these proposed strategies.Moreover, we explore the bearing-only formation for nonlinear multi-agent systems. A compensation function is established in the controller to eliminate the effect of the unknown nonlinear items in the system. This compensation function is also based on bearing measurements, which ensures that the overall controller is bearing-only. By using the Lyapunov techniques, the formation tracking error will converge to zero exponentially under the proposed bearing-only algorithm. Moreover, we investigate the performance of the protocol for moving leaders, where the formation tracking error can be restricted in a bounded set. Finally, the simulation results are presented to validate the feasibility of the proposed algorithm for both fixed and moving leaders.Finally, an SDP-based robust formation-containment coordination is proposed for swarm robotic systems with input saturation. A novel control protocol and an implementation algorithm are proposed that enable the leaders to achieve the desired formation via SDP techniques. The followers then converge into the convex hull formed by the leaders simultaneously. Both single-integrator dynamics and double-integrator dynamics are considered in the controller design. We conduct the simulations to verify the formation-containment algorithm and analyse some of the factors that affected the formation-containment performance. The proposed algorithm is also applied to a real-world scenario by performing an experiment using multiple mobile robots.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798382652757Subjects--Topical Terms:

657657
Digital cameras.
Index Terms--Genre/Form:

554714
Electronic books.

Distributed Formation Control in Swarm Robotics.
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500 $a Source: Dissertations Abstracts International, Volume: 85-11, Section: B.
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502 $a Thesis (Ph.D.)--The University of Manchester (United Kingdom), 2023.
504 $a Includes bibliographical references
520 $a Inspired by natural swarm collective behaviours such as colonies of bees and schools of fish, coordination strategies in swarm robotics have received significant attention in recent years. Distributed control on formation aims to coordinate a team of robots to form a desired geometric pattern through local information, which is a hot topic in swarm intelligence. The main objective of this thesis is to construct formation algorithms combined with bearing measurements for multi-robot systems and provide applications in real robotic scenarios.First, we establish a basic formation framework based on edge and bearing measurements for networked multi-robot systems. The edge-based and bearing-based protocols are combined in controller design to maximise the advantages of both methods. We discuss the robustness of the mixed controller for both leaderless and leader-follower cases by Lyapunov approach. Simulation case studies are also presented to verify the effectiveness of the theoretical results.Furthermore, a bearing-only collision-free formation coordination strategy is proposed for networked heterogeneous robots, where each robot only measures the relative bearings of its neighbours to achieve cooperation. Different from many existing studies that can only guarantee global asymptotic stability, a gradient-descent control protocol is designed to make the robots achieve a target formation within a given finite time. The stability of the multi-robot system is guaranteed via Lyapunov theory, and the convergence time can be defined by users. The exogenous disturbances in the system and actuator faults in the controller are also considered in convergence analysis. Then, the proposed finite-time bearing-only protocol is extended to linear time-invariant systems. Numerical simulations and lab-based experiments using unmanned ground vehicles are conducted to validate the effectiveness of these proposed strategies.Moreover, we explore the bearing-only formation for nonlinear multi-agent systems. A compensation function is established in the controller to eliminate the effect of the unknown nonlinear items in the system. This compensation function is also based on bearing measurements, which ensures that the overall controller is bearing-only. By using the Lyapunov techniques, the formation tracking error will converge to zero exponentially under the proposed bearing-only algorithm. Moreover, we investigate the performance of the protocol for moving leaders, where the formation tracking error can be restricted in a bounded set. Finally, the simulation results are presented to validate the feasibility of the proposed algorithm for both fixed and moving leaders.Finally, an SDP-based robust formation-containment coordination is proposed for swarm robotic systems with input saturation. A novel control protocol and an implementation algorithm are proposed that enable the leaders to achieve the desired formation via SDP techniques. The followers then converge into the convex hull formed by the leaders simultaneously. Both single-integrator dynamics and double-integrator dynamics are considered in the controller design. We conduct the simulations to verify the formation-containment algorithm and analyse some of the factors that affected the formation-containment performance. The proposed algorithm is also applied to a real-world scenario by performing an experiment using multiple mobile robots.
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650 4 $a Communication. $3 556422
650 4 $a Sensors. $3 1003702
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650 4 $a Unmanned aerial vehicles. $3 1372845
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650 4 $a Vehicles. $3 721652
650 4 $a Aerospace engineering. $3 686400
650 4 $a Transportation. $3 558117
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