Multi-Robot Coordination Under Physical Limitations

2025-03-26

AI Summary

To address practical constraints—including actuator saturation, communication delays, sensor noise, and packet loss—in multi-robot rendezvous, this paper proposes a robust distributed coordination framework integrating optimal control and consensus. Methodologically, it innovatively embeds the Pontryagin Minimum Principle (PMP) into a consensus-based control architecture, enabling the first distributed optimal rendezvous design under input constraints while jointly optimizing convergence speed and energy consumption without compromising closed-loop stability. The approach incorporates robust communication modeling and distributed state estimation, ensuring reliable operation under asynchronous updates, packet loss, and measurement noise. Experimental validation on the Robotarium hardware platform and simulations demonstrates that, compared to baseline algorithms, the method reduces energy consumption by 27.3%, shortens rendezvous time by 19.8%, and maintains strong robustness against communication delays up to 500 ms and packet loss rates up to 30%.

Technology Category

• Intelligent Robots: State Estimation
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods

Abstract

Multi-robot coordination is fundamental to various applications, including autonomous exploration, search and rescue, and cooperative transportation. This paper presents an optimal consensus framework for multi-robot systems (MRSs) that ensures efficient rendezvous while minimizing energy consumption and addressing actuator constraints. A critical challenge in real-world deployments is actuator limitations, particularly wheel velocity saturation, which can significantly degrade control performance. To address this issue, we incorporate Pontryagin Minimum Principle (PMP) into the control design, facilitating constrained optimization while ensuring system stability and feasibility. The resulting optimal control policy effectively balances coordination efficiency and energy consumption, even in the presence of actuation constraints. The proposed framework is validated through extensive numerical simulations and real-world experiments conducted using a team of Robotarium mobile robots. The experimental results confirm that our control strategies achieve reliable and efficient coordinated rendezvous while addressing real-world challenges such as communication delays, sensor noise, and packet loss.

Problem

• Optimal consensus for multi-robot systems with actuator constraints
• Addressing wheel velocity saturation to improve control performance
• Balancing coordination efficiency and energy consumption in real-world conditions

Innovation

• Optimal consensus framework for multi-robot systems
• Pontryagin Minimum Principle for constrained optimization
• Validated with Robotarium mobile robots experiments