Path Planning of a Mobile Robot Using Real-coded Genetic Algorithm Based Simultaneous Exploration
Chih-Jer Lin, Yen-Lin Chen, Cheng-Hsin Liu, Shenkai Yu
Available Online July 2013.
- https://doi.org/10.2991/cse.2013.22How to use a DOI?
- Labview, real-coded genetic algorithm, path planning, mobile robot
- In mobile robot researches, path planning and obstacle avoidance plays a very important role and has been a very challenging research topic. For path planning, it should produce continuous path from the starting point to the destination without colliding obstacles. Therefore, we proposes a genetic algorithm to search the path with the shortest path in Labview environment. The difficulty of the genetic algorithms applied to the mobile robot is how to reduce the complexity of the genetic operations, and how to avoid the region optimal solution and adaptation of environmental change. Many researchers studied genetic algorithms to determine the optimal solution such as path planning, but the past literatures mostly used binary coding for the gene encoding. If the path is longer or the number of obstacles is larger, the binary coding will be a lengthy string of series. This will result in the longer evolution of computing time. As a result, we propose a novel method which is a serial number encoded as a gene encoding to effectively reduce the evolution of computing time for the path planning applications.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Chih-Jer Lin AU - Yen-Lin Chen AU - Cheng-Hsin Liu AU - Shenkai Yu PY - 2013/07 DA - 2013/07 TI - Path Planning of a Mobile Robot Using Real-coded Genetic Algorithm Based Simultaneous Exploration BT - 2nd International Conference on Advances in Computer Science and Engineering (CSE 2013) PB - Atlantis Press SP - 91 EP - 94 SN - 1951-6851 UR - https://doi.org/10.2991/cse.2013.22 DO - https://doi.org/10.2991/cse.2013.22 ID - Lin2013/07 ER -