Sensor-based path planning for nonholonomic mobile robots subject to dynamic constraints

It is generally not easy to achieve smooth path planning in an unknown environment for nonholonomic mobile robots, which are subject to various robot constraints. In this paper, a hybrid approach is proposed for smooth path planning with global convergence for differential drive nonholonomic robots. We first investigate the use of a polar polynomial curve (PPC) to produce a path changing continuously in curvature and satisfying dynamic constraints. In order to achieve path generation in real-time, a computationally effective method is proposed for collision test of the complex curve. Then, a hybrid path planning approach is presented to guide the robot to move forward along the boundary of an obstacle of arbitrary shape, by generating a proper “Instant Goal” (and a series of deliberate motions through PPC curve based path generation) and planning reactively when needed using a fuzzy controller for wall following. The choice of an Instant Goal is limited to the set of candidates that are practically reachable by the robot and that enable the robot to continue following the obstacle. The effectiveness of the proposed approach is verified by simulation experiments.