POA: Passable Obstacles Aware Path-planning Algorithm for Navigation of a Two-wheeled Robot in Highly Cluttered Environments

TL;DR

The paper introduces POA, a novel path-planning algorithm for two-wheeled robots that effectively navigates highly cluttered environments by distinguishing passable obstacles, reducing path length and travel time significantly.

Contribution

It presents a new navigation method that detects and classifies obstacles, enabling robots to pass through passable obstacles and improve path efficiency in cluttered spaces.

Findings

Reduces path length by up to 43%

Decreases total travel time by up to 39%

Effective in highly cluttered environments

Abstract

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*