Cooperative-ORCA*: Real-Time Proactive Deadlock Avoidance for Continuous-Space Multi-Agent Navigation

2026-06-21

AI Summary

This work addresses the deadlock problem in continuous-space multi-agent navigation caused by myopic decision-making. The authors propose the C-ORCA* family of algorithms, which integrates agents’ full predicted trajectories and their spatial dependencies into real-time velocity planning to enable proactive deadlock avoidance. Notably, C-ORCA* is the first approach in continuous-space Multi-Agent Path Finding (MAPF) to eliminate traditional reactive fallback mechanisms by actively preventing conflicts through trajectory prediction. Experimental results demonstrate that C-ORCA* significantly outperforms state-of-the-art methods across three key metrics: solution success rate, computation time, and total path duration.

Abstract

Multi-Agent Path Finding (MAPF) is a problem that requires computing collision-free paths for a set of agents from their start locations to designated goal locations. The problem has broad applications in domains where teams of robots must operate in a coordinated manner. ORCA* is a real time MAPF solver that assigns for each timestep a velocity for each agent. Due to its real time nature, it is myopic to future deadlocks that result from current decisions. ORCA*-MAPF attempts to remedy this limitation by introducing fallback mechanisms when deadlocks are detected. However, post hoc interventions often introduce significant flowtime overhead. In this paper, we introduce C-ORCA* and C-ORCA*-MAPF, continuous space MAPF algorithms that incorporate agents' entire spatial trajectory and their spatial dependencies to proactively prevent deadlocks from occurring, thus avoiding the high flowtime overhead associated with post hoc corrections in ORCA*-MAPF. The C-ORCA* family of algorithms significantly outperform previous state-of-the-art in terms of solve rate, runtime, and flowtime.

Problem

• Multi-Agent Path Finding
• deadlock avoidance
• continuous space
• real-time navigation
• flowtime overhead

Innovation

• Cooperative-ORCA*
• deadlock avoidance
• multi-agent path finding
• continuous space
• proactive planning