ABSTRACT 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. GRAPHICAL ABSTRACT

中文翻译：

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基于链路参数估计的自适应基于虚拟功率的碰撞检测和隔离

摘要 我们提出了一种自适应的基于虚拟功率的碰撞检测和隔离方法，用于具有链接参数估计的机器人操纵器。使用估计的虚拟速度和接触力获得功率指数。功率指标的有效性依赖于对链路参数的精确了解，而这通常很难获得。因此，在本文中，我们提出了一系列使用链路参数估计方案的自适应功率指标，以增加对参数不确定性的鲁棒性。为了使用所提出的方法显示碰撞检测和隔离的统计性能，我们使用 2 自由度 (DOF) 实验机械手执行多个接触任务，同时考虑链接参数的不确定性，并且可以正确检测和隔离2-DOF机械手每个链接上发生的大多数碰撞。此外，还分别比较了基于模型和自适应功率指标的碰撞检测和碰撞隔离。利用自适应功率指标，可以平滑地确定碰撞检测的唯一阈值；同时，正确的碰撞隔离率增加。图形概要