Task Allocation and Motion Planning in Dynamic, Cluttered Environments via CBBA and Graphs of Convex Sets
This paper presents a solution combining Graphs of Convex Sets (GCS) for trajectory optimization and the Consensus-Based Bundle Algorithm (CBBA) for distributed task allocation in multi-agent systems. GCS finds optimal trajectories in a 3D+time configuration space, while CBBA coordinates task assignments, enabling collision avoidance and accurate time estimates. Effectiveness is demonstrated in simulated cluttered environments with static and dynamic tasks.
[2606.18516] Task Allocation and Motion Planning in Dynamic, Cluttered Environments via CBBA and Graphs of Convex Sets
[Submitted on 16 Jun 2026]
Title:Task Allocation and Motion Planning in Dynamic, Cluttered Environments via CBBA and Graphs of Convex Sets
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Abstract:Multi-agent task planning in cluttered, dynamic environments requires assigning tasks to agents while simultaneously determining safe, time-efficient trajectories through the environment. When tasks are dynamic, such as rendezvous objectives, allocation decisions depend not only on which agent is best suited for a task, but also on when and where that task can be reached. This paper presents a solution to this problem, which combines Graphs of Convex Sets (GCS) for trajectory optimization with the Consensus-Based Bundle Algorithm (CBBA) for distributed task allocation. In our approach, GCS finds optimal trajectories through dynamic environments using a time-extended (3D+time) configuration space. At the same time, CBBA coordinates task assignments across agents, enabling informed decision-making in a moving environment. We then connect allocation and planning to allow the agents to avoid collisions in the 3D+time configuration space and provide accurate time estimates for task completion. We demonstrate the effectiveness of our approach in simulated cluttered environments with static and dynamic tasks.
Comments: 15 pages single column, 10 figures, AIAA-Scitech 2027 Submission
Subjects:
Robotics (cs.RO)
Cite as: arXiv:2606.18516 [cs.RO]
(or arXiv:2606.18516v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2606.18516
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Matthew Osburn [view email] [v1] Tue, 16 Jun 2026 22:14:15 UTC (430 KB)
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