Performance of a Wall-Following Robot Controlled by a PID-BA using Bat Algorithm Approach

A wall-following robot needs a controller that applies the closed-loop concept to move actively without hindrance. Some controllers with good capabilities can act as controllers for wall follower robots, such as PID controllers. Conceptually, this controller's good performance depends on tuning the three gains before use. Instead of giving the expected and appropriate output, wrong settings will provide inaccuracies for the controller, so applying the manual method at the tuning stage is not recommended. For this reason, PID controllers are often implemented in a system supported by appropriate optimization methods, such as Genetic Algorithm or Particle Swarm Optimization. Furthermore, different from this, in this study, the Bath Algorithm is used as an alternative optimization algorithm. Its application begins with a realistic simulation of a wall-following robot. This is done to provide the possibility to implement online PID controllers and BAs. In the end, several methods are compared to find out the performance of this type of approach. Moreover, based on the observed comparative results, the proposed method gives a better value in accumulative error and convergence speed in the PID optimization process.