Tompos, Dénes and Hegedűs, Tamás and Németh, Balázs (2025) Advanced Motion Planning Method for Unmanned Vehicles to Consider 3D Objects. LECTURE NOTES IN MECHANICAL ENGINEERING, ICMCE. pp. 87-93. ISSN 2195-4356 10.1007/978-981-96-6452-8_7

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Abstract

This paper proposes a motion planning method which focuses on the consideration of moving 3D objects along the route of the unmanned vehicles. The goal of the method is to detect conflict situations and to avoid collisions to the objects. The proposed method continuously recognizes conflict situations using a clustering algorithm. The motion planning with a reinforcement-learning-based (RL) agent is facilitated, which can result in efficient and collision-free motion. The effectiveness of the method is illustrated on the route planning for an unmanned drone, which has to fly in an area with moving obstacles. © 2025 Elsevier B.V., All rights reserved.

Item Type:	Article
Uncontrolled Keywords:	motion planning; reinforcement learning; soft computing; Unmanned aerial vehicles (UAV); Computer vision; Clustering algorithms; 3D object; Unmanned vehicles; Clusterings; Collision-Free; conflict situation; motion-planning; Reinforcement learnings; Point-clouds; Motion planning methods; Clustering point clouds; Safe motion; Clustering point cloud; Safe motion;
Subjects:	Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions:	Systems and Control Lab
SWORD Depositor:	MTMT Injector
Depositing User:	MTMT Injector
Date Deposited:	24 Jan 2026 08:41
Last Modified:	24 Jan 2026 08:41
URI:	https://eprints.sztaki.hu/id/eprint/11093

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