Deadlock-free, safe, and decentralized multi-robot navigation in social mini-games via discrete-time control barrier functions

Abstract We present an approach to ensure safe and deadlock-free navigation for decentralized multi-robot systems operating in constrained environments, including doorways and intersections. Although many solutions have been proposed that ensure safety and resolve deadlocks, optimally preventing deadlocks in a minimally invasive and decentralized fashion remains an open problem. We first formalize the objective as a non-cooperative, non-communicative, partially observable multi-robot navigation problem in constrained spaces with multiple conflicting agents, which we term as social mini-games. Formally, we solve a discrete-time optimal receding horizon control problem leveraging control barrier functions for safe long-horizon planning. Our approach to ensuring liveness rests on the insight that there exists barrier certificates that allow each robot to preemptively perturb their state in a minimally-invasive fashion onto liveness sets i.e. states where robots are deadlock-free . We evaluate our approach in simulation as well on physical robots using F1/10 robots, a Clearpath Jackal, as well as a Boston Dynamics Spot in a doorway, hallway, and corridor intersection scenario. Compared to both fully decentralized and centralized approaches with and without deadlock resolution capabilities, we demonstrate that our approach results in safer, more efficient, and smoother navigation, based on a comprehensive set of metrics including success rate, collision rate, stop time, change in velocity, path deviation, time-to-goal, and flow rate.

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Publication Details

Journal
Autonomous Robots
Published
2025-04-20
DOI
https://doi.org/10.1007/s10514-025-10194-8
Citations
5
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
7.44

Funders

Controls
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article

Deadlock-free, safe, and decentralized multi-robot navigation in social mini-games via discrete-time control barrier functions

Peter Stone, Joydeep Biswas, Rohan Chandra, Vrushabh Zinage et al.
5 citations
Autonomous Robots
Distributed Control Multi-Agent Systems
7.44
article

Deadlock-free, safe, and decentralized multi-robot navigation in social mini-games via discrete-time control barrier functions

Peter Stone, Joydeep Biswas, Rohan Chandra, Vrushabh Zinage, Efstathios Bakolas
article en
5 citations

Abstract

Abstract We present an approach to ensure safe and deadlock-free navigation for decentralized multi-robot systems operating in constrained environments, including doorways and intersections. Although many solutions have been proposed that ensure safety and resolve deadlocks, optimally preventing deadlocks in a minimally invasive and decentralized fashion remains an open problem. We first formalize the objective as a non-cooperative, non-communicative, partially observable multi-robot navigation problem in constrained spaces with multiple conflicting agents, which we term as social mini-games. Formally, we solve a discrete-time optimal receding horizon control problem leveraging control barrier functions for safe long-horizon planning. Our approach to ensuring liveness rests on the insight that there exists barrier certificates that allow each robot to preemptively perturb their state in a minimally-invasive fashion onto liveness sets i.e. states where robots are deadlock-free . We evaluate our approach in simulation as well on physical robots using F1/10 robots, a Clearpath Jackal, as well as a Boston Dynamics Spot in a doorway, hallway, and corridor intersection scenario. Compared to both fully decentralized and centralized approaches with and without deadlock resolution capabilities, we demonstrate that our approach results in safer, more efficient, and smoother navigation, based on a comprehensive set of metrics including success rate, collision rate, stop time, change in velocity, path deviation, time-to-goal, and flow rate.

Autonomous RobotsVol. 49(2)
Sony Corporation (United States) (US), University of Virginia (US), The University of Texas at Austin (US)
National Science Foundation, University of Texas at Austin, Office of Naval Research, Division of Civil, Mechanical and Manufacturing Innovation, Army Research Office
Openalex Percentile: Top 3%
Distributed Control Multi-Agent Systems
7.44
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