Supernumerary robotic devices in the form of wearable arms enhance a user's reachable workspace and provide them with additional capabilities. However, the user may experience considerable force and moment loads on their body due to the robot's motion. In this letter, we present a simulation and trajectory planning framework that aims to minimize the load on a user's muscles while operating a Wearable Robotic Forearm (WRF). Using a high-fidelity model of the human arm, we construct a term for biomechanical costs that is subsequently added to the overall cost function for a motion planner. For evaluation, the planner is initialized with shortest paths linearly interpolated between ten start and goal state pairs in the configuration space, as well as with paths optimized for reaction moments using a local search. We find that the biomechanical planner coupled with locally-optimized initialization reduces mean human muscle fiber forces by up to 23.47% compared to the linearly interpolated trajectories.

中文翻译：

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可穿戴机器人前臂的生物力学运动规划


可穿戴手臂形式的额外机器人设备增强了用户可触及的工作空间，并为他们提供了额外的功能。然而，由于机器人的运动，用户的身体可能会承受相当大的力和力矩负载。在这封信中，我们提出了一个模拟和轨迹规划框架，旨在最大限度地减少用户在操作可穿戴机器人前臂（WRF）时肌肉的负荷。使用人类手臂的高保真模型，我们构建了一个生物力学成本术语，随后将其添加到运动规划器的总体成本函数中。为了进行评估，规划器使用配置空间中十个起始状态对和目标状态对之间线性插值的最短路径以及使用局部搜索针对反应时刻优化的路径进行初始化。我们发现，与线性插值轨迹相比，生物力学规划器与局部优化初始化相结合，可将平均人体肌纤维力降低高达 23.47%。