This paper considers the problem of safely coordinating a team of sensor-equipped robots to reduce uncertainty about a dynamical process, where the objective trades off information gain and energy cost. Optimizing this trade-off is desirable, but leads to a non-monotone objective function in the set of robot trajectories. Therefore, common multi-robot planners based on coordinate descent lose their performance guarantees. Furthermore, methods that handle non-monotonicity lose their performance guarantees when subject to inter-robot collision avoidance constraints. As it is desirable to retain both the performance guarantee and safety guarantee, this work proposes a hierarchical approach with a distributed planner that uses local search with a worst-case performance guarantees and a decentralized controller based on control barrier functions that ensures safety and encourages timely arrival at sensing locations. Via extensive simulations, hardware-in-the-loop tests and hardware experiments, we demonstrate that the proposed approach achieves a better trade-off between sensing and energy cost than coordinate-descent-based algorithms.

翻译：本文研究如何安全协调一组搭载传感器的机器人团队，以降低对动态过程的不确定性，目标在信息获取与能量成本之间进行权衡。优化该权衡虽具理想性，但会导致机器人轨迹集合上的非单调目标函数。因此，基于坐标下降的常见多机器人规划器会丧失性能保证。此外，当面临机器人间碰撞避免约束时，处理非单调性的方法会失去性能保证。鉴于同时保留性能保证与安全保证的可取性，本工作提出一种分层方法：首先采用具有最坏情况性能保证的分布式局部搜索规划器，其次基于控制屏障函数设计分散式控制器，以保障安全性并促进机器人及时抵达传感位置。通过大规模仿真、硬件在环测试及硬件实验，我们证明所提方法相比坐标下降类算法能实现传感与能量成本之间更优的权衡。