PointsBug versus TangentBug algorithm, a performance comparison in unknown static environment

摘要

This paper presents an overview of Bug algorithm family local path planning methodology timeline. The Bug algorithm approach detects the nearest obstacle as a mobile robot moves towards a target with limited information about the environment. It uses obstacle border as guidance toward the target. The robot circumnavigates the obstacle till it finds certain condition to fulfill the algorithm criteria to leave the obstacle towards target point. In addition, this paper presents the performance of a new path planning approach, PointsBug algorithm. The performance of PointsBug was compared to TangentBug in term of duration and distance in various types of environment. TangentBug was selected as the algorithm to be compared to as it is the best performing Bug family algorithm that uses a range sensor similar to PointsBug. The outcomes of the research indicates that PointsBug have outperformed TangentBug in average speed in the selected environment as described in this paper.