Mobile manipulators have gained attention for the potential in performing large-scale tasks which are beyond the reach of fixed-base manipulators. The Robotic Task Sequencing Problem for mobile manipulators often requires optimizing the motion sequence of the robot to visit multiple targets while reducing the number of base placements. A two-step approach to this problem is clustering the task-space into clusters of targets before sequencing the robot motion. In this paper, we propose a task-space clustering method which formulates the clustering step as a Set Cover Problem using bipartite graph and reachability analysis, then solves it to obtain the minimum number of target clusters with corresponding base placements. We demonstrated the practical usage of our method in a mobile drilling experiment containing hundreds of targets. Multiple simulations were conducted to benchmark the algorithm and also showed that our proposed method found, in practical time, better solutions than the existing state-of-the-art methods.

翻译：移动机械臂因其在执行超出固定基座机械臂范围的大规模任务中的潜力而受到关注。移动机械臂的机器人任务排序问题通常需要优化机器人的运动序列，以在减少基座放置次数的同时访问多个目标。解决该问题的一种两步法是将任务空间中的目标聚类成簇，然后再排序机器人运动。本文提出了一种任务空间聚类方法，该方法利用二分图与可达性分析将聚类步骤形式化为集合覆盖问题，并通过求解得到具有对应基座放置的最小目标簇数量。我们在一次包含数百个目标的移动钻孔实验中展示了该方法的实际应用。通过多项仿真实验对算法进行了基准测试，结果表明，所提方法能在实际可行时间内找到优于现有最优方法的解。