A Method for Robot Motor Fatigue Management in Physical Interaction and Human-Robot Collaboration Tasks
A Method for Robot Motor Fatigue Management in Physical Interaction and Human-Robot Collaboration Tasks
复制标题
物理交互和人机协作任务中机器人电机疲劳管理的方法
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
A. Ajoudani
中科院分区：
文献类型：
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作者：
L. Peternel;N. Tsagarakis;A. Ajoudani
协作机器人通常设计为具有有限的功率和力容量，旨在提供负担得起的解决方案，并在意外碰撞和冲击的情况下确保人类安全。如果任务需要超过此容量的功率，或者长时间重复执行，则可能会超过这些限制，这可能会导致不可避免的机器人损坏并导致生产力损失。在这种情况下，硬件解决方案和改进不适用，有效的软件框架可以延长机器人的生产力和寿命。为此，在本文中，我们提出了一种新的技术，在重复或高努力的任务执行情况下的机器人疲劳的监测和管理。通过测量关节电机的温度来估计机器人的疲劳。建议的疲劳管理系统是由两个阶段的反应过程，这是由不同程度的估计疲劳触发。第一阶段利用机器人结构的运动学冗余，试图通过笛卡尔任务生产的零空间在关节空间中重新配置来最小化在疲劳下的特定关节中的负载。如果第一阶段在减少疲劳方面不成功，则激活第二阶段，逐渐减少混合控制器的力。此时，人类同事可以暂时接管任务执行，直到机器人从过度疲劳中恢复过来。为了验证所提出的方法，我们在KUKA轻型机器人上进行了实验，执行两项交互任务：自主表面擦拭和协作人机表面抛光。
Collaborative robots are often designed with limited power and force capacity, with the aim to provide affordable solutions and ensure human safety in case of accidental collisions and impacts. If a task requires a power beyond this capacity, or is performed repeatedly over long periods, such limits may be exceeded, which can cause inevitable robot damage and contribute to the lost productivity. In such cases, where hardware solutions and improvements are not applicable, effective software frameworks can prolong robot productivity and lifetime. To this end, in this paper we propose a novel technique for the monitoring and management of robot fatigue in repetitive or high-effort task execution scenarios. The robot fatigue is estimated by the measured temperature of motors in the joints. The proposed fatigue management system is composed of two-stage reaction process that is triggered by different levels of the estimated fatigue. The first stage exploits the kinematic redundancy of robot structure in attempt to minimise the load in the specific joints that under fatigue by reconfiguration in the joint space through the null space of the Cartesian task production. If the first stage is not successful in reducing the fatigue, the second stage is activated that gradually reduces the forces of hybrid controller. At that point, the human co-worker can temporarily take over the task execution until the robot will be recovered from the excessive fatigue. To validate the proposed approach we conducted experiments on KUKA Lightweight Robot performing two interaction tasks: autonomous surface wiping and collaborative human-robot surface polishing.