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.

翻译：多机器人系统的一个关键挑战在于如何在确保安全性的同时兼顾精度与效率。现有方法无法严格保证任意数量机器人的无碰撞运行，或结果过于保守。避障轨迹的平滑性亦有待进一步优化。本文针对任意规模机器人集群，提出一种加速度驱动的同步避障与轨迹跟踪方法，该策略提供非保守的碰撞避免机制并给出死锁规避方案。我们提出两种死锁消解途径：其一是将辅助速度矢量引入轨迹跟踪模块的误差函数，该方法被证明不影响跟踪误差的全局收敛性；此外，区别于传统方法在死锁发生后处理冲突的机制，我们的决策系统能规避近零速度状态，在密集环境中具有更高安全性与运行效率。大量对比实验表明，所提方法在大规模机器人系统中部署时较现有研究具有显著优势，且系统侵入性极低。