Human Intention-Aware Motion Planning and Adaptive Fuzzy Control for a Collaborative Robot With Flexible Joints

This paper presents a framework to enable a human and a robot to perform collaborative tasks safely and efficiently. It consists of three functions. First, human motion is predicted by utilizing Gaussian mixture regression. Second, an online robot motion planning is performed such that the robot can appropriately react to the human co-worker while executing a task. In our proposed framework, the predicted human motion is transferred to a virtual force acting on a robot's end-effector. Its initial trajectory is modified so as to avoid any collisions with the human. To obtain a smooth, collision-free and energy-minimized trajectory, a constrained optimization problem is formulated. A neural dynamics optimization algorithm is then adopted to solve it. Third, an adaptive fuzzy controller is proposed to track the robot's desired trajectory with uncertain dynamics parameters. Moreover, we also provide the rigorous proof of stability for the proposed methods. The physical experiments are conducted to demonstrate the effectiveness of the proposed collaborative strategy.