A Perception-Decision-Control Framework for Dynamic Obstacle Avoidance of UAVs

DOI

10.2991/978-94-6463-821-9_118How to use a DOI?

Keywords

Unmanned Aerial Vehicle; Obstacle Avoidance; Linear Temporal Logic; Dijkstra Algorithm; PID Control

Abstract

Unmanned aerial vehicles (UAVs) face significant challenges in dynamic obstacle avoidance despite their broad applications in agriculture, logistics, and emergency response. Existing methods, such as sampling-based RRT and graph-based Dijkstra algorithms, often struggle with dynamic environments and complex multi-objective tasks. This study proposes an integrated ″perception-decision-control″ framework to address these limitations. The framework incorporates multi-sensor fusion (LiDAR, vision, IMU) for robust environmental perception, linear temporal logic (LTL) for task decomposition and constraint formalization, and an improved Dijkstra algorithm with safety constraints for real-time path planning. A PID-based tracking controller ensures precise trajectory execution, achieving a 95% success rate in dynamic obstacle avoidance scenarios, with trajectory errors below 0.30.3 m. Experimental validation on a quadrotor platform demonstrates enhanced adaptability to illumination variations and computational efficiency (45 FPS on embedded hardware). The system provides a comprehensive solution for autonomous UAV navigation, balancing safety, real-time performance, and mission complexity. Future work will focus on adaptive control strategies and multi-agent coordination to further improve robustness in large-scale environments.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Chen Chen
PY  - 2025
DA  - 2025/08/31
TI  - A Perception-Decision-Control Framework for Dynamic Obstacle Avoidance of UAVs
BT  - Proceedings of the 2025 2nd International Conference on Mechanics, Electronics Engineering and Automation (ICMEEA 2025)
PB  - Atlantis Press
SP  - 1253
EP  - 1261
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-821-9_118
DO  - 10.2991/978-94-6463-821-9_118
ID  - Chen2025
ER  -