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| Content Provider | Springer Nature Link |
|---|---|
| Author | Sameshima, Katsumichi Naka, Kazushi Funato, Tetsuro Hosokawa, Shu |
| Copyright Year | 2014 |
| Abstract | Path planning in various situations is an essential ability for a useful mobile robot in the real world, and technologies facilitating this have been tested in the RoboCup soccer leagues. The main difficulty in path planning lies in the presence of (mobile) obstacles and the kinematic and computational constraints of robots. Rapidly exploring random trees (RRTs) and spatio-temporal RRTs (StRRTs) are popular algorithms for mobile robots in the small size league, one of the RoboCup’s soccer leagues. In these algorithms, paths of finite length are randomly generated in each time interval, and adequate paths among these are selected. Thus, path length and selection probability are important factors. In this paper, we propose a method to determine these parameters using particle swarm optimization. The proposed method is examined using simulations and its real-time tuning ability is verified. The automatically tuned controllers are also capable of real-time path planning through a mobile robot with limited computational ability, such as those used in RoboCup. |
| Starting Page | 388 |
| Ending Page | 393 |
| Page Count | 6 |
| File Format | |
| ISSN | 14335298 |
| Journal | Artificial Life and Robotics |
| Volume Number | 19 |
| Issue Number | 4 |
| e-ISSN | 16147456 |
| Language | English |
| Publisher | Springer Japan |
| Publisher Date | 2014-11-12 |
| Publisher Place | Tokyo |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Path planning RRT StRRT PSO Automatic parameter tuning Artificial Intelligence (incl. Robotics) Computation by Abstract Devices Control, Robotics, Mechatronics |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Biochemistry, Genetics and Molecular Biology |
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