Key areas of robot agility include methods that increase capability and flexibility of industrial robots and facilitate robot re-tasking. Manual guidance can achieve robot agility effectively, provided that a safe and smooth interaction is guaranteed when the user exerts an external force on the end effector. We approach this by designing an adaptive admittance law that can adjust its parameters to modify the robot compliance in critical areas of the workspace, such as near and on configuration singularities, joint limits, and workspace limits, for a smooth and safe operation. Experimental validation was done with two tests: a constraint activation test and a 3D shape tracing task. In the first one, we validate the proper response to constraints and in the second one, we compare the proposed approach with different admittance parameter tuning strategies using a drawing task where the user is asked to guide the robot to trace a 3D profile with an accuracy or speed directive and evaluate performance considering path length error and execution time as metrics, and a questionnaire for user perception. Results show that appropriate response to individual and simultaneous activation of the aforementioned constraints for a safe and intuitive manual guidance interaction is achieved and that the proposed parameter tuning strategy has better performance in terms of accuracy, execution time, and subjective evaluation of users.

机器人敏捷性的关键领域包括提高工业机器人的能力和灵活性并促进机器人重新分配任务的方法。手动引导可以有效地实现机器人的敏捷性，前提是当用户在末端执行器上施加外力时确保安全，顺畅的交互。我们通过设计一种自适应导纳法则来解决此问题，该法则可以调整其参数以修改工作区关键区域（如配置奇异点，关节极限和工作空间极限附近和之上）的机器人顺从性，从而实现平稳安全的操作。实验验证通过两项测试完成：约束激活测试和3D形状跟踪任务。在第一个中，我们验证对约束的正确响应，在第二个中，我们使用绘图任务将建议的方法与不同的导纳参数调整策略进行比较，其中要求用户引导机器人以精度或速度指令来跟踪3D轮廓，并以路径长度误差和执行时间为度量标准来评估性能，以及用户感知问卷。结果表明，可以实现对上述约束的单独激活和同时激活的适当响应，以实现安全，直观的手动引导交互，并且所提出的参数调整策略在准确性，执行时间和用户的主观评价方面具有更好的性能。