This work develops a novel trajectory planner for human-robot handovers. The handover requirements can naturally be handled by a path-following-based model predictive controller, where the path progress serves as a progress measure of the handover. Moreover, the deviations from the path are used to follow human motion by adapting the path deviation bounds with a handover location prediction. A Gaussian process regression model, which is trained on known handover trajectories, is employed for this prediction. Experiments with a collaborative 7-DoF robotic manipulator show the effectiveness and versatility of the proposed approach.

翻译：本文开发了一种面向人-机器人交接的新型轨迹规划器。交接需求可通过基于路径跟踪的模型预测控制器自然处理，其中路径进度作为交接过程的进度度量。此外，通过利用交接位置预测自适应调整路径偏差边界，路径偏差被用于跟随人体运动。采用基于已知交接轨迹训练的高斯过程回归模型实现该预测。通过与七自由度协作机械臂的实验，验证了所提方法的有效性与通用性。