An Enhanced Navigation Algorithm with an Adaptive Controller for Wheeled Mobile Robot Based on Bidirectional RRT

Abstract

A navigation algorithm providing motion planning for two-wheeled mobile robots is proposed in this paper. The motion planning integrates path planning, velocity planning and controller design. Bidirectional rapidly-exploring random trees algorithms (RRT) with path pruning and smoothing mechanism are firstly used to obtain a collision-free path to the robot destination with directional continuity. Secondly, velocity planning based on trapezoidal velocity profile is used in both linear and angular velocities, but the position error of the endpoint of the curve appears due to the coupling problem of the nonlinear system. To reduce the error, an approximation method is used to gradually modify several parts of time length of the trapezoidal velocity profile, so the continuity of the path can still be maintained. Thirdly, the controller keeping the robot on the planned path and velocity is designed based on the dynamic model of the robot. The parameters of this controller are estimated by the adaptive low, and the gain of controller is dynamic adjusted by fuzzy logic control to avoid the case that the control value is saturated. The controller stability and the convergence of tracking error is guaranteed by Lyapunov theory. Simulation results are presented to illustrate the effectiveness and efficiency.