Integrated Multi-UAV Motion Planning Under Kinematic Constraints Based on Enhanced Conflict-Based Search

Multi-uncrewed aerial vehicle (UAV) performing tasks in obstacle-intensive aerospace environments requires prior motion planning to mitigate real-time tracking and control challenges. However, conventional hierarchical motion planning often leads to secondary conflicts and other issues. In this lett...

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Bibliographic Details
Published in:IEEE robotics and automation letters Vol. 10; no. 12; pp. 13050 - 13057
Main Authors: Li, Liya, Liu, Yucong, Qi, Guoyuan, Ahn, Choon Ki
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.12.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Aerospace environments
Autonomous aerial vehicles
Collision avoidance
Constraints
Cost function
Costs
enhanced conflict-based search (ECBS)
Heuristic algorithms
Kinematics
Motion planning
Multi-UAV motion planning
Obstacle avoidance
Optimization
Prediction algorithms
Real time
receding horizon optimization (RHO)
Searching
Trajectories
Trajectory
Trajectory optimization
Unmanned aerial vehicles
ISSN:2377-3766, 2377-3766
Online Access:Get full text
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Summary:Multi-uncrewed aerial vehicle (UAV) performing tasks in obstacle-intensive aerospace environments requires prior motion planning to mitigate real-time tracking and control challenges. However, conventional hierarchical motion planning often leads to secondary conflicts and other issues. In this letter, we address the multi-UAV motion planning problem by explicitly considering their unique kinematic constraints, as well as the collision avoidance and obstacle avoidance problems in complex environments. First, we propose an integrated enhanced conflict-based search (ECBS) framework that employs a front-end and back-end unified approach to generate final trajectories while avoiding secondary conflicts directly. Second, we couple segmented trajectories with low-level search nodes by incorporating trajectory states into the cost function. Receding horizon optimization (RHO) is used to generate continuous and smooth trajectories that satisfy the UAV kinematic constraints. In addition, methods for resolving continuous conflicts in discrete spaces are designed. Finally, simulation results demonstrate the validity of the proposed algorithm and the effectiveness of the generated trajectories.
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ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2025.3627094