Finite-Time Coverage Control for Multiagent Systems With Unidirectional Motion on a Closed Curve

Area of Science:

• Robotics and Control Systems
• Networked Multi-Agent Systems
• Optimization Theory

Background:

• Networked mobile agents face challenges in achieving efficient coverage due to continuous-time dynamics and motion constraints.
• Minimizing the largest arrival time to any point on a closed curve is a key objective in coverage control problems.

Purpose of the Study:

• To solve the finite-time coverage control problem for networked mobile agents with continuous-time dynamics and unidirectional motion constraints.
• To design distributed low-gain feedback control laws that minimize a coverage cost function in finite time.

Main Methods:

• Development of distributed coverage control laws using low-gain feedback, accommodating agents with varying input constraints.
• Analysis of agent distances to establish lower and upper bounds, informing the derivation of gain upper bounds.
• Leveraging the property that at least one agent remains static due to unidirectional motion to refine gain bounds.

Main Results:

• The proposed control laws successfully drive networked mobile agents to an optimal configuration, minimizing the coverage cost function in finite time.
• An upper bound on low gains is derived, ensuring bounded inter-agent distances.
• A less conservative upper bound on low gains is obtained, enhancing convergence rates.

Conclusions:

• The study presents an effective approach for finite-time coverage control in constrained multi-agent systems.
• The derived control laws and gain bounds offer improved performance and convergence for networked mobile agents.
• The findings contribute to the advancement of distributed control strategies for complex robotic systems.