Optimal path planning algorithm for swarm robots using bat algorithm with mutation (bam) - Lim, Pei Yee (2022)
In robot navigation, path planning is always the most crucial problem where robots should be able to move from starting position to goal position without colliding into any obstacle. This is because robot is unable to plan an optimum path in a known situation and obstacles available increases the difficulty for robot to move according to the planned path in an environment. The current research in robot navigation is to implement an obstacle avoidance algorithm to a single mobile robot to realize the path planning of a mobile robot. However, there is still room for improvement such as implementing the obstacle avoidance algorithm into swarm robot. The objective of this study is to propose Bat Algorithm with Mutation (BAM) for solving the problem of obstacle avoidance of mobile robots. This project is completed by creating a wheeled mobile robot where the robot uses a P controller. Next, robot is trained to travel from one point to another point and inserted into a virtual environment with static obstacle. The obstacle avoidance algorithm is then implemented to the robot. Lastly, it can be seen that the robot is able to move in the planned path without colliding with the obstacle in the environment.