Dexterous manipulation of objects once held in hand remains a challenge. Such skills are, however, necessary for robotics to move beyond gripper-based manipulation and use all the dexterity offered by anthropomorphic robotic hands. One major challenge when manipulating an object within the hand is that fingers must move around the object while avoiding collision with other fingers or the object. Such collision-free paths must be computed in real-time, as the smallest deviation from the original plan can easily lead to collisions. We present a real-time approach to computing collision-free paths in a high-dimensional space. To guide the exploration, we learn an explicit representation of the free space, retrievable in real-time. We further combine this representation with closed-loop control via dynamical systems and sampling-based motion planning and show that the combination increases performance compared to alternatives, offering efficient search of feasible paths and real-time obstacle avoidance in a multi-fingered robotic hand.

翻译：手持物体后的灵巧操作仍是一项挑战。然而，这类技能对于机器人超越基于夹爪的操作模式、充分利用拟人化机械手所具备的灵巧性至关重要。在手内操作物体时的主要难点在于：手指需在避免与其他手指或物体发生碰撞的同时围绕物体移动。此类无碰撞路径必须实时计算，因为与原始规划的微小偏差极易导致碰撞。我们提出一种在高维空间中实时计算无碰撞路径的方法。为引导探索过程，我们学习了一种可实时检索的自由空间显式表示。进一步地，我们将该表示与通过动态系统和基于采样的运动规划实现的闭环控制相结合，实验表明该组合方案相比替代方法性能更优，能够高效搜索可行路径并在多指机械手场景中实现实时避障。