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Research PaperResearchia:202605.12083

Decentralized Contingency MPC based on Safe Sets for Nonlinear Multi-agent Collision Avoidance

Max Studt

Abstract

Decentralized collision avoidance remains challenging, particularly when agents do not communicate any information related to planned trajectories. Most existing approaches either rely on conservative coordination mechanisms or provide limited guarantees on recursive feasibility and convergence. This paper develops a decentralized contingency MPC framework for multi-agent systems with nonlinear dynamics that achieves collision-free motion under a state-only information pattern. Each agent follow...

Submitted: May 12, 2026Subjects: Robotics; Robotics

Description / Details

Decentralized collision avoidance remains challenging, particularly when agents do not communicate any information related to planned trajectories. Most existing approaches either rely on conservative coordination mechanisms or provide limited guarantees on recursive feasibility and convergence. This paper develops a decentralized contingency MPC framework for multi-agent systems with nonlinear dynamics that achieves collision-free motion under a state-only information pattern. Each agent follows the same consensual rule set, enabling safe decentralized planning without communication. Each agent solves a local optimization problem that couples a nominal trajectory with a contingency certificate ensuring a feasible backup maneuver under receding-horizon operation. A novel geometric and decentralized safe-set update mechanism prevents feasibility loss between consecutive time steps. The resulting scheme guarantees recursive feasibility, including collision avoidance, and establishes a Lyapunov-type convergence result to an admissible safe equilibrium. Simulation results demonstrate performance in both sparse and dense multi-agent environments, including cluttered bottleneck scenarios and under plug-and-play operation.


Source: arXiv:2605.10738v1 - http://arxiv.org/abs/2605.10738v1 PDF: https://arxiv.org/pdf/2605.10738v1 Original Link: http://arxiv.org/abs/2605.10738v1

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Submission Info
Date:
May 12, 2026
Topic:
Robotics
Area:
Robotics
Comments:
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