POA: Passable Obstacles Aware Path-planning Algorithm for Navigation of a Two-wheeled Robot in Highly Cluttered Environments
This addresses path-planning challenges for two-wheeled robots in highly cluttered environments, offering a domain-specific incremental improvement over existing methods.
The paper tackles navigation for two-wheeled robots in cluttered environments by introducing a Passable Obstacles Aware (POA) planner that classifies obstacles as passable or unpassable, enabling robots to find paths through passable obstacles, resulting in up to 43% shorter path lengths and 39% reduced travel time compared to standard planners.
This paper focuses on Passable Obstacles Aware (POA) planner - a novel navigation method for two-wheeled robots in a highly cluttered environment. The navigation algorithm detects and classifies objects to distinguish two types of obstacles - passable and unpassable. Our algorithm allows two-wheeled robots to find a path through passable obstacles. Such a solution helps the robot working in areas inaccessible to standard path planners and find optimal trajectories in scenarios with a high number of objects in the robot's vicinity. The POA planner can be embedded into other planning algorithms and enables them to build a path through obstacles. Our method decreases path length and the total travel time to the final destination up to 43% and 39%, respectively, comparing to standard path planners such as GVD, A*, and RRT*