The notion of safety in multi-agent systems assumes great significance in many emerging collaborative multi-robot applications. In this paper, we present a multi-UAV collaborative target-tracking application by defining bounded inter-UAV distances in the formation in order to ensure safe operation. In doing so, we address the problem of prioritizing specific objectives over others in a multi-objective control framework. We propose a barrier Lyapunov function-based distributed control law to enforce the bounds on the distances and assess its Lyapunov stability using a kinematic model. The theoretical analysis is supported by numerical results, which account for measurement noise and moving targets. Straight-line and circular motion of the target are considered, and results for quadratic Lyapunov function-based control, often used in multi-agent multi-objective problems, are also presented. A comparison of the two control approaches elucidates the advantages of our proposed safe-control in bounding the inter-agent distances in a formation. A concluding evaluation using ROS simulations illustrates the practical applicability of the proposed control to a pair of multi-rotors visually estimating and maintaining their mutual separation within specified bounds, as they track a moving target.
翻译:多试剂系统的安全概念在许多新出现的多机器人协作应用中具有重大意义。在本文件中,我们提出了一个多无人驾驶航空器协作目标跟踪应用,方法是在编队中界定受约束的无人驾驶航空器间距离,以确保安全运行;在这样做时,我们处理在多目标控制框架内将具体目标置于其他具体目标之上的问题;我们提出了一个基于Lyapunov屏障功能的分布式控制法,以采用动态模型执行距离界限并评估其Lyapunov稳定性;理论分析得到数字结果的支持,该结果考虑到测量噪音和移动目标;考虑目标的直线和圆形运动,并介绍在多试剂多目标问题中经常使用的四边形Lyapunov功能控制结果;对两种控制方法进行比较,说明我们提议的安全控制在编队中将机构间距离捆绑方面的好处;利用ROS模拟进行的最后评价,说明拟议控制对一组多式机器人的实际适用性,对它们在指定界限内进行视觉估计和保持相互分离,作为目标的轨道。