Obstacle Avoidance for Swarm Robot Based on Self-Organizing Migrating Algorithm
| Autor: | Diep Quoc Bao, Ivan Zelinka |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Fitness function
Computer science Swarm behaviour 020206 networking & telecommunications 02 engineering and technology Computer Science::Robotics Position (vector) Obstacle avoidance 0202 electrical engineering electronic engineering information engineering Trajectory General Earth and Planetary Sciences Robot 020201 artificial intelligence & image processing Set (psychology) Algorithm General Environmental Science |
| Zdroj: | Procedia Computer Science. 150:425-432 |
| ISSN: | 1877-0509 |
| Popis: | This paper presents an obstacle avoidance algorithm for swarm robot in unknown environment based on self-organizing migrating algorithm in which the trajectory is divided into a set of points created by the SOMA that robot must pass through. During the move, obstacles will be detected by sensors on the robot, it only knows the target position without knowing the obstacles location until detecting them. The fitness function is based on the principle of attraction from the target and the repulsion of the obstacles, which helps robot find the trajectory for moving, and the ways leaving it to move safety away from the trapped area. Simulation results are also presented to show the feasibility of the algorithm. |
| Databáze: | OpenAIRE |
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