An Improved Algorithm for Collision Avoidance in Environments Having U and H Shaped Obstacles

This paper proposes a novel obstacle avoidance algorithm for autonomous mobile robot control. The proposed approach brings a solution to the problem of robot traversal in critical shaped environments and offers several advantages compared to the reported approaches. The algorithmic approach, named as, Intelligent Follow the Gap Method (IFGM) is based on improved Intelligent Bug Algorithm (IBA) and Follow the Gap Method (FGM). The robot field of view is taken into consideration. The IBA avoids obstacles by following their edge and scanning the path to destination, thus making the approach goal-oriented avoiding local minimum problem. To characterize the performance of IFGM, various scenarios of obstacles are considered. These scenarios range from having obstacles defined by simple and symmetrical shapes to critical shaped obstacles. The simulation results demonstrate that the algorithm results in safer and smoother trajectories in the presence of obstacles. It offers fast convergence and does not suffer from local minima. Finally, the performance comparison of the proposed algorithm with that of the reported approaches in terms of distance-time plots confirms the efficacy of the presented approach. The proposed algorithm lends itself to future implementations in the navigation of mobile and industrial robots, especially in applications exhibiting crucial time and critical obstacles including disaster management, spy, elderly people assistance and soccer games.