With the aim of further enabling the exploitation of intentional impacts in robotic manipulation, a control framework is presented that directly tackles the challenges posed by tracking control of robotic manipulators that are tasked to perform nominally simultaneous impacts. This framework is an extension of the reference spreading control framework, in which overlapping ante- and post-impact references that are consistent with impact dynamics are defined. In this work, such a reference is constructed starting from a teleoperation-based approach. By using the corresponding ante- and post-impact control modes in the scope of a quadratic programming control approach, peaking of the velocity error and control inputs due to impacts is avoided while maintaining high tracking performance. With the inclusion of a novel interim mode, we aim to also avoid input peaks and steps when uncertainty in the environment causes a series of unplanned single impacts to occur rather than the planned simultaneous impact. This work in particular presents for the first time an experimental evaluation of reference spreading control on a robotic setup, showcasing its robustness against uncertainty in the environment compared to three baseline control approaches.

翻译：为了进一步实现机器人操作中利用有意碰撞的目标，本文提出了一种控制框架，直接应对机器人机械臂在执行名义上同步碰撞任务时跟踪控制所面临的挑战。该框架是参考扩展控制框架的扩展，其中定义了与碰撞动力学一致的前后碰撞重叠参考轨迹。在本工作中，此类参考轨迹的构建始于一种基于遥操作的方法。通过在二次规划控制方法的框架内使用相应的前后碰撞控制模式，避免了由碰撞引起的速度误差和控制输入的峰值，同时保持了高跟踪性能。通过引入一种新颖的中间模式，我们还旨在避免当环境不确定性导致一系列非计划单次碰撞（而非计划的同步碰撞）发生时产生的输入峰值和阶跃。本工作特别首次在机器人实验平台上对参考扩展控制进行了实验评估，展示了其相较于三种基线控制方法对环境不确定性的鲁棒性。