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Weight-Incorporating A* Algorithm with Multi-Factor Cost Function for Enhanced Mobile Robot Path Planning

Jae Hwan Bong, Seongkyun Jeong

Year
2025
Citations
4
Access
Open access

Abstract

This study proposes the Weight-Incorporating A* (WIA*) algorithm for mobile robot path planning. The WIA* algorithm integrates three weight factors into the Conventional A* cost function: an Obstacle Collision (OC) weight factor for collision avoidance, a Path Distance (PD) weight factor for path length optimization, and a Driving Suitability (DS) weight factor for environmental considerations. Experimental validation was conducted using nine 2D grid maps and a 3D virtual environment. The results show that WIA* achieved zero obstacle collisions compared to an average of 9.11 collisions with Conventional A*. Although WIA* increased path length by 12.69%, it reduced driving suitability cost by 93.88%, achieving zero cost in six out of nine test environments. The algorithm demonstrates effective collision-free path generation while incorporating environmental factors for practical mobile robot navigation.

Keywords

Motion planningMobile robotComputer scienceFactor (programming language)Function (biology)AlgorithmPath (computing)RobotMathematical optimizationArtificial intelligence

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