Design and Implementation of Path Planning for Wheel-Track Hybrid Mobile Robot

Abstract

Wheel-track hybrid mobile robot has been widely used because of its high autonomous mobility and its ability to adapt to complex and changeable outdoor environment. Map construction and path planning are the main conditions to achieve its autonomous mobility. Therefore, a wheel-track hybrid robot path planning has been designed and implemented. Simultaneous Localization and Mapping (SLAM) algorithms are used to process the road images captured by the robot's camera and other sensors. A rapid raster map with Robot Operating System (ROS) was constructed by rapid recognition of key elements from the images with the help of the Oriented Fast and Rotated Brief (ORB) feature vector. The ant colony algorithm with strong optimization ability, high optimization efficiency, and flexible algorithm is used for path planning, and the problem of unfixed location of outdoor obstacles is solved at the same time. The simulation results show that the global performance and convergence speed of the improved algorithm are increased.