Trajectory Tracking Control of a Differential-Drive Mobile Robot

Proper control techniques are required for autonomous mobile robots to find the right path in a dynamic environment. In this work, a Grey Wolf Optimization (GWO) for tuning the adaptive proportional-integral-derivative (PID) controller has been implemented for the TurtleBot3 in a simulated environment created using Gazebo and ROS 2. The GWO and conventional Ziegler-Nichols (ZN) based PID controllers are compared to check the flexibility of different control systems and to minimize errors in the trajectory. The performance parameters of trajectory deviation, the settling time and the control efforts have been illustrated. An enhanced Bug Zero algorithm has also been used for path planning along with the above techniques to get accurate results where it has been incorporated with a laser-based obstacle detection mechanism which helps to avoid obstacles. Thus, this paper elaborates on the metaheuristic optimization techniques that can be helpful for adaptive PID tuning for robotic applications such as an intelligent control strategy for autonomous navigation of mobile robots in the real world.