Autonomous motion planning for obstacles-climbing of a multi-track robot

To improve the autonomous ability, the obstacles-climbing module of a searching robot under mine disasters is built. Based on the model, the ability of obstacles-climbing robot is analyzed and an nested artificial fish-swarm algorithm (NAFSA) is developed to solve the automatic motion planning of the robot. The method adopts the AFAS in three layers of four groups which can weaken the coupling of the four variables, and uses the rapidly random exploring method for reducing the variables bounds to meet with the minimum changes of joint angles. Then, simulations in MATLAB show that this method can get the key joint angles more effectively and in less intervals than traditional method, and provide reference for the robot control. Finally, the obstacle-climbing experiment of double units mode is carried out, and the simulation result verifies that the robot can climb over the obstacle.