We propose an adaptive virtual power-based collision detection and isolation approach for robotic manipulators with link parameter estimation. The power indexes are obtained using estimated virtual velocities and contact forces. The effectiveness of the power indexes is relied on precise knowledge of link parameters, which is commonly difficult to obtain. Therefore, in this paper, we propose a series of adaptive power indexes using a link parameter estimation scheme, in order to increase the robustness to parameter uncertainties. To show the statistical performance of collision detection and isolation using the proposed approach, we conduct multiple contact tasks using a 2 degree of freedom (DOF) experimental manipulator while considering uncertainties of the link parameters, and most collisions occurred on each link of the 2-DOF manipulator can be correctly detected and isolated. Additionally, the model-based and adaptive power indexes are compared for collision detection and collision isolation, respectively. Using the adaptive power indexes, the unique threshold can be smoothly determined for collision detection; meanwhile, the correct collision isolation rate increases.

我们提出了一种具有链接参数估计的基于自适应虚拟功率的机械手碰撞检测和隔离方法。使用估计的虚拟速度和接触力获得功率指数。功率指标的有效性取决于链路参数的精确知识，而这通常很难获得。因此，在本文中，我们使用链路参数估计方案提出了一系列自适应功率指标，以提高对参数不确定性的鲁棒性。为了显示使用所提出的方法进行碰撞检测和隔离的统计性能，我们在考虑链接参数不确定性的情况下，使用2自由度（DOF）实验操纵器执行多个接触任务，并且可以正确检测和隔离在2-DOF机械手的每个链接上发生的大多数碰撞。此外，比较了基于模型的功率指数和自适应功率指数，分别用于碰撞检测和碰撞隔离。使用自适应功率指标，可以平滑确定唯一阈值以进行碰撞检测；同时，正确的碰撞隔离率也会提高。