Aiming at the defects of low sampling efficiency and high deviation from optimal solutions of basic RRT algorithm due to randomly selecting extended nodes, an improved RRT algorithm with goal-biased is proposed. After the extended nodes being selected by using the target bias strategy and the odor diffusion, random trees grow to target points. A path smoothing method based on B-spline curve is proposed, which has higher searching efficiency and path quality. The simulation results demonstrate that the path generated by the proposed algorithm is around 22.1% shorter than that of basic RRT algorithm and the path is smoother as well. Furthermore, the proposed algorithm has stronger ability of avoiding obstacles. Finally, the improved RRT algorithm is applied it to Turtlebot2 in real environment. The experimental results illustrate that the improved RRT algorithm achieves higher reliability and practicability.

%U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.1903-0105