Generating on-purpose impacts with rigid robots is challenging as they may lead to severe hardware failures due to abrupt changes in the velocities and torques. Without dedicated hardware and controllers, robots typically operate at a near-zero velocity in the vicinity of contacts. We assume knowing how much of impact the hardware can absorb and focus solely on the controller aspects. The novelty of our approach is twofold: (i) it uses the task-space inverse dynamics formalism that we extend by seamlessly integrating impact tasks; (ii) it does not require separate models with switches or a reset map to operate the robot undergoing impact tasks. Our main idea lies in integrating post-impact states prediction and impact-aware inequality constraints as part of our existing general-purpose whole-body controller. To achieve such prediction, we formulate task-space impacts and its spreading along the kinematic tree of a floating-base robot with subsequent joint velocity and torque jumps. As a result, the feasible solution set accounts for various constraints due to expected impacts. In a multi-contact situation of under-actuated legged robots subject to multiple impacts, we also enforce standing stability margins. By design, our controller does not require precise knowledge of impact location and timing. We assessed our formalism with the humanoid robot HRP-4, generating maximum contact velocities, neither breaking established contacts nor damaging the hardware.

翻译：有意图地利用刚性机器人产生冲击具有挑战性，因为速度和力矩的突变可能导致严重的硬件故障。在缺乏专门硬件和控制器的情况下，机器人通常以接近零的速度在接触区域附近运行。我们假设已知硬件可承受的冲击能力，并聚焦于控制器设计。本方法的新颖性体现在两方面：(i) 采用任务空间逆动力学形式，通过无缝集成冲击任务进行扩展；(ii) 无需为冲击任务切换单独模型或重置映射即可控制机器人。核心思想在于将冲击后状态预测与冲击感知不等式约束整合到现有通用全身控制器中。为实现预测，我们推导了任务空间冲击及其沿浮动基座机器人运动学链的传播规律及相应的关节速度与力矩跃变。据此，可行解集合涵盖了预期冲击带来的各类约束。针对受多冲击作用欠驱动机器人的多点接触问题，我们还强制保证了站立稳定性裕度。该控制器无需获知冲击的精确位置与时间。通过人形机器人HRP-4验证表明，本方法在未破坏既有接触或损坏硬件的前提下，可生成最大接触速度。