论文标题
在机器人目标方面允许安全接触：在操作和空空间中进行计划和跟踪
Allowing Safe Contact in Robotic Goal-Reaching: Planning and Tracking in Operational and Null Spaces
论文作者
论文摘要
近年来，机器人操作中已经取得了令人印象深刻的结果。尽管许多努力着重于产生无冲突的参考信号，但很少有机器人机构与环境之间的安全接触。但是，在人类的日常操纵中，武器和障碍之间的接触是普遍的，甚至是必要的。本文研究了在机器人操作过程中允许安全接触的好处，并提倡在操作和无空间中生成和跟踪依从性信号。此外，为了优化相撞允许的轨迹，我们提出了一个集成基于采样和梯度方法的混合求解器。我们在具有不同碰撞条件的五个模拟和现实世界中的目标任务中评估了拟议方法。我们表明，允许安全联系可以提高目标的效率，并在无法执行无碰撞约束的高度碰撞方案中提供可行的解决方案。此外，我们证明，除操作空间外，在零空间中的计划可提高轨迹安全。
In recent years, impressive results have been achieved in robotic manipulation. While many efforts focus on generating collision-free reference signals, few allow safe contact between the robot bodies and the environment. However, in human's daily manipulation, contact between arms and obstacles is prevalent and even necessary. This paper investigates the benefit of allowing safe contact during robotic manipulation and advocates generating and tracking compliance reference signals in both operational and null spaces. In addition, to optimize the collision-allowed trajectories, we present a hybrid solver that integrates sampling- and gradient-based approaches. We evaluate the proposed method on a goal-reaching task in five simulated and real-world environments with different collisional conditions. We show that allowing safe contact improves goal-reaching efficiency and provides feasible solutions in highly collisional scenarios where collision-free constraints cannot be enforced. Moreover, we demonstrate that planning in null space, in addition to operational space, improves trajectory safety.
