Abstract
The Expanded Douglas–Peucker (EDP) polygonal approximation algorithm and its application method for the Opposite Angle-Based Exact Cell Decomposition (OAECD) are proposed for the mobile robot path-planning problem with curvilinear obstacles. The performance of the proposed algorithm is compared with the existing Douglas–Peucker (DP) polygonal approximation and vertical cell decomposition algorithm. The experimental results show that the path generated by the OAECD algorithm with EDP approximation appears much more natural and efficient than the path generated by the vertical cell decomposition algorithm with DP approximation.
Highlights
The path-planning process of a mobile robot aims at finding a collision-free path to move the robot from the current posture to the goal posture [1,2,3]
Two types of experiments were conducted to find the performance of the proposed Expanded Douglas–Peucker (EDP) and modified Opposite Angle-Based Exact Cell Decomposition (OAECD) algorithm
An additional simulation has been performed to verify the feasibility of the modified OAECD algorithm for a map with curvilinear obstacles
Summary
The path-planning process of a mobile robot aims at finding a collision-free path to move the robot from the current posture to the goal posture [1,2,3]. Cell decomposition, which is a classical and representative method for mobile-robot path planning, decomposes the given environment into several cells and finds a collision-free path based on the connectivity graph of these cells [2,3,4,5,6,7,8,9,10]. Sci. 2019, 9, 638 increases the efficiency in path planning, but finding the optimal decomposition case is known as an NP-hard problem [1,2,3]. Reducing the number of decomposed cells directly increases the efficiency in path planning, to OAECD path planning to the cases with curvilinear obstacles. Algorithm for the application curvilinear obstacles is proposed with mathematical validation on
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