提出一种无需保守假设的多机器人避障轨迹跟踪方法。
Collision Risk Quantification and Conflict Resolution in Trajectory Tracking for Acceleration-Actuated Multi-Robot Systems
- 基于加速度控制实现避障与轨迹跟踪同步
- 可处理任意规模机器人队列且避免死锁
- 在密集环境更安全高效，适合大规模部署
多机器人系统中如何兼顾精度、效率与安全是关键挑战。现有方法无法严格保证任意大规模机器人群体的无碰撞，或结果过于保守，且避障轨迹平滑性有待提升。本文提出一种面向任意大规模机器人团队的加速度驱动式协同避障与轨迹跟踪方法，提供非保守的碰撞规避策略，并给出死锁避免方案。提出两种死锁解决方式，其中一种通过在轨迹跟踪误差函数中引入辅助速度向量，证明其不影响全局跟踪误差收敛性。不同于传统方法在死锁发生后才处理冲突，本方法的决策机制主动避免接近零速度状态，在密集环境中更安全高效。大量对比实验表明，该方法在大规模机器人系统部署中优于现有研究，且干预程度最小。
原文摘要 · Abstract (English)
One of the pivotal challenges in a multi-robot system is how to give attention to accuracy and efficiency while ensuring safety. Prior arts cannot strictly guarantee collision-free for an arbitrarily large number of robots or the results are considerably conservative. Smoothness of the avoidance trajectory also needs to be further optimized. This paper proposes an accelerationactuated simultaneous obstacle avoidance and trajectory tracking method for arbitrarily large teams of robots, that provides a nonconservative collision avoidance strategy and gives approaches for deadlock avoidance. We propose two ways of deadlock resolution, one involves incorporating an auxiliary velocity vector into the error function of the trajectory tracking module, which is proven to have no influence on global convergence of the tracking error. Furthermore, unlike the traditional methods that they address conflicts after a deadlock occurs, our decision-making mechanism avoids the near-zero velocity, which is much more safer and efficient in crowed environments. Extensive comparison show that the proposed method is superior to the existing studies when deployed in a large-scale robot system, with minimal invasiveness.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。