We present a reactive base control method that enables high performance mobile manipulation on-the-move in environments with static and dynamic obstacles. Performing manipulation tasks while the mobile base remains in motion can significantly decrease the time required to perform multi-step tasks, as well as improve the gracefulness of the robot's motion. Existing approaches to manipulation on-the-move either ignore the obstacle avoidance problem or rely on the execution of planned trajectories, which is not suitable in environments with dynamic objects and obstacles. The presented controller addresses both of these deficiencies and demonstrates robust performance of pick-and-place tasks in dynamic environments. The performance is evaluated on several simulated and real-world tasks. On a real-world task with static obstacles, we outperform an existing method by 48\% in terms of total task time. Further, we present real-world examples of our robot performing manipulation tasks on-the-move while avoiding a second autonomous robot in the workspace. See https://benburgesslimerick.github.io/MotM-BaseControl for supplementary materials.

翻译：我们提出了一种反应式基座控制方法，可在包含静态与动态障碍物的环境中实现高性能的移动操作。在移动基座保持运动的同时执行操作任务，能够显著减少完成多步骤任务所需的时间，同时提升机器人运动的流畅性。现有的移动操作方法要么忽略避障问题，要么依赖预规划轨迹的执行——这并不适用于具有动态物体和障碍物的环境。本文提出的控制器解决了这两个缺陷，并在动态环境中展示了稳健的拾取与放置任务性能。该性能通过多个仿真与现实世界任务进行评估。在包含静态障碍物的真实任务中，我们的方法在总任务时间上比现有方法提升48%。此外，我们展示了机器人执行移动操作任务时，成功避让工作空间中另一台自主机器人的真实场景实例。补充材料请参见 https://benburgesslimerick.github.io/MotM-BaseControl。