OGPR: An Obstacle-Guided Path Refinement Approach for Mobile Robot Path Planning

• Published in: 2018 IEEE International Conference on Robotics and Biomimetics (ROBIO) pp. 844 - 849
• Main Authors: B. Atia, Mohamed G., Salah, Omar, Ei-Hussieny, Haitham
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2018
• Subjects: Mathematical model; Mobile robots; Path planning; Planning; Shape; Time factors
• DOI: 10.1109/ROBIO.2018.8665080

Despite the emergence of the available path planning approaches for mobile robots, excessive computation time have remained an open issue, especially in time-critical scenarios. In this paper, however, an Obstacle-Guided Path Refinement (OGPR) approach is developed to plan a set of short collision-free paths between the start and the target points for mobile robots. A particle swarm optimization framework has been adopted to retrieve the obstacles geometry and subsequently refine the line-of-sight path connecting the start and the target points. The developed OGPR approach has assessed over a 2D simulation environment and the results show that its effectiveness in planning safe paths shorter than the state-of-the-art A* algorithm. This, in fact, could encourage further application of the proposed OGPR approach in future in 3D spatial environments.