Distributed Nash Equilibrium Seeking Algorithm in Aggregative Games for Heterogeneous Multi-Robot Systems

2025/09/19 by Yi Dong, Dong, Yi, Zhongguo Li +5
Computer Science · Engineering · #Distributed Control Multi-Agent Systems #FOS: Computer and information sciences #Guidance and Control Systems #Robotics (cs.RO)

paper · pdf · doi:10.48550/arxiv.2509.15597

openalex publication_date 2025/09/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper develops a distributed Nash Equilibrium seeking algorithm for heterogeneous multi-robot systems. The algorithm utilises distributed optimisation and output control to achieve the Nash equilibrium by leveraging information shared among neighbouring robots. Specifically, we propose a distributed optimisation algorithm that calculates the Nash equilibrium as a tailored reference for each robot and designs output control laws for heterogeneous multi-robot systems to track it in an aggregative game. We prove that our algorithm is guaranteed to converge and result in efficient outcomes. The effectiveness of our approach is demonstrated through numerical simulations and empirical testing with physical robots.

Citations

• Probabilistic Game-Theoretic Traffic Routing
• Multi-UAV Planning for Cooperative Wildfire Coverage and Tracking with Quality-of-Service Guarantees
• Fast Contact-Implicit Model-Predictive Control
• UAV-Based Search and Rescue in Avalanches using ARVA: An Extremum Seeking Approach
• Distributed stochastic optimization with gradient tracking over strongly-connected networks
• Distributed averaging integral Nash equilibrium seeking on networks
• Geometric Convergence of Gradient Play Algorithms for Distributed Nash\n Equilibrium Seeking
• Distributed Algorithms for Aggregative Games on Graphs
• Distributed Nash Equilibrium Seeking by A Consensus Based Approach
• Fast Distributed Gradient Methods
• Distributed Stochastic Subgradient Projection Algorithms for Convex Optimization

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