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October 16, 2025Open Access

MRBTP: Efficient Multi-Robot Behavior Tree Planning and Collaboration

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Authors

YCYishuai CaiKing UniversityXCXinglin ChenShanghai University of Traditional Chinese MedicineZCZhongxuan CaiNational University of Defense Technology

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Overview

Proposed MRBTP algorithm improves task planning and collaboration in multi-robot systems, indicating efficiency gains with LLM integration.

Key Points

  • MRBTP demonstrates improved efficiency and execution in multi-robot task planning, with soundness and completeness guarantees.
  • Evaluation in warehouse management and service scenarios shows robustness, with LLM-enhanced planning significantly speeding up tasks.
  • The algorithm uniquely coordinates diverse action spaces, making it suitable for both homogeneous and heterogeneous robot teams.
  • By utilizing intention sharing, MRBTP reduces redundant executions and enhances the reliability of multi-robot collaboration.

Cite This Study

Cai et al. (2025) studied this question.

synapsesocial.com/papers/68f0d5eb105731330a2b2129https://doi.org/10.48550/arxiv.2502.18072
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Integrating Intent Understanding and Optimal Behavior Planning for Behavior Tree Generation from Human Instructions2024 · 1 citations
  2. 2BTPG: A Platform and Benchmark for Behavior Tree Planning in Everyday Service Robots2025
  3. 3Efficient Behavior Tree Planning with Commonsense Pruning and Heuristic2024
  4. 4Code-BT: A Code-Driven Approach to Behavior Tree Generation for Robot Tasks Planning with Large Language Models2025
  5. 5LLM-BT: Performing Robotic Adaptive Tasks based on Large Language Models and Behavior Trees2024