Path planning and obstacle avoidance for a robot with large degree of redundancy

John Zhao Li, University of Nevada, Las Vegas


An algorithm to allow a redundant robot to avoid obstacles in its workspace is proposed. The task of path planning is formulated as a sequence of nonlinear programming problems. For each problem, the objective is to minimize the distance between the current location of the end-effector and some intermediate point along a desired path. Two penalties are added to the objective function to ensure that the robot is not colliding with an obstacle and that its links are intersecting one another. Inequality constraints describing the mechanical stops and limiting values for joint movements are incorporated. Obstacles are represented as polygons, which are composed of series of connecting line segments. Successive quadratic programming algorithm is used to solve the path planning problem. To save computation time, the algorithm activates the joints that are closer to the end effector. If activations of those joints cannot satisfactory complete the task, other joints will be sequentially mobilized until the desired path is reached. The proposed method is demonstrated especially efficient when the degrees of freedom are large.