Obstacle‐responsive navigation scheme of a wheeled mobile robot based on look‐ahead control
Yu Yu Lwin, Yoshio Yamamoto
- 发表年份
- 2012
- 引用次数
- 5
摘要
Purpose The purpose of this paper is to design a mobile robot controller which is able to pursue a given goal with obstacle‐avoiding capability in which the two tasks, i.e. aiming at the goal and avoiding obstacles, are fused together in a coherent framework of look‐ahead control method. Design/methodology/approach Navigation toward a goal is typically executed based on global information obtained from GPS. Obstacle avoidance, however, is local in nature, and a higher priority temporarily should be placed on avoiding a collision with the obstacle than taking the shortest path toward the goal. The former is handled by the goal‐aiming mode while the latter is dealt with by the obstacle‐avoiding mode. These two tasks with different natures are treated under so‐called “look‐ahead control” by simply changing coordinate frames and associated elements within the same controller. Therefore, continuity and smoothness of the resulting motion and trajectory is maintained throughout its mission. Findings Two different tasks, goal aiming and collision avoiding, can smoothly be switched back and forth within the same controller by replacing its coordinate frame, decoupling matrix and corresponding reference signals to follow. It is found through simulation and real experiments that the proposed scheme can graciously handle obstacles, static or dynamic, regardless of the number of obstacles. Also, the look‐ahead control guarantees smoothness of resulting trajectories. Originality/value Mobile robot autonomous navigation in outdoor obstructed areas offers challenging study for robot researchers. The vital aspect is to smartly control the mobile robot to move to the desired location autonomously, without colliding with any obstacles. The proposed method provides a stable and robust navigation framework for any kind of mobile robot, especially for outdoor use.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991