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Agoraphilic-3D: A Novel Algorithm for Robot Path Planning in Mapless Uneven Terrains

W. M. D. Gunathilaka,G. Kahandawa,M. Y. Ibrahim,H. Hewawasam,Linh Nguyen

Published 2025 in IEEE Access

ABSTRACT

Autonomous ground robot navigation in unstructured, mapless, and uneven terrains remains a challenging task due to variable slopes, environmental occlusions, and the need to preserve robot stability. To address these challenges, this paper presents Agoraphilic-3D (A3D), a novel path planning algorithm designed for real-world, uneven terrain navigation with explicit consideration of stability constraints. A3D extends the free space based navigation concept of the original Agoraphilic algorithm, advancing it from 2D environment navigation to 3D environment navigation. The proposed algorithm introduces a Square Sector Map (SS-Map), a robot-centric grid representation of 3D point cloud data, which enables efficient terrain analysis and free space determination. An unsupervised clustering-based occlusion filtering method is incorporated to remove ambiguous regions, producing cleaner data for terrain feature extraction. Using the SS-Map together with the filtered data, the terrain slope is assessed relative to the robot’s stability constraints, defined by its maximum allowable pitch and roll angles, and encoded into a 1D free space histogram. Based on this representation, free-space attractive forces are derived to guide navigation through the most stable regions, while a steering factor mechanism simultaneously biases the trajectory toward the goal. Extensive experiments in both simulation and real-world outdoor environments demonstrate the effectiveness of the A3D algorithm. The results highlight its robustness in identifying terrain variations, filtering unstable regions, and generating safe, traversable paths without reliance on prior maps. Overall, A3D provides a practical and adaptable framework for autonomous ground navigation in challenging domains such as exploration, agriculture, and search and rescue.

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