UAV-based Receding Horizon Control for 3D Inspection Planning

Abstract

Nowadays, unmanned aerial vehicles or UAVs are being used for a wide range of tasks, including infrastructure inspection, automated monitoring and coverage. This paper investigates the problem of 3D inspection planning with an autonomous UAV agent which is subject to dynamical and sensing constraints. We propose a receding horizon 3D inspection planning control approach for generating optimal trajectories which enable an autonomous UAV agent to inspect a finite number of feature-points scattered on the surface of a cuboid-like structure of interest. The inspection planning problem is formulated as a constrained open-loop optimal control problem and is solved using mixed integer programming (MIP) optimization. Quantitative and qualitative evaluation demonstrates the effectiveness of the proposed approach.

arXiv comment2022 International Conference on Unmanned Aircraft Systems (ICUAS), 21-24 June 2022, Dubrovnik, Croatia

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Cited by in corpus (12)

• Distributed Search Planning in 3-D Environments With a Dynamically Varying Number of Agents
• Distributed Control for 3D Inspection using Multi-UAV Systems
• Unscented Optimal Control for 3D Coverage Planning with an Autonomous UAV Agent
• Integrated Ray-Tracing and Coverage Planning Control using Reinforcement Learning
• Model Predictive Control For Multiple Castaway Tracking with an Autonomous Aerial Agent
• VLM-RRT: Vision Language Model Guided RRT Search for Autonomous UAV Navigation
• Cooperative Receding Horizon 3D Coverage Control with a Team of Networked Aerial Agents
• Automated Real-Time Inspection in Indoor and Outdoor 3D Environments with Cooperative Aerial Robots
• Synergising Human-like Responses and Machine Intelligence for Planning in Disaster Response
• Jointly-optimized Trajectory Generation and Camera Control for 3D Coverage Planning
• Hierarchical Fault-Tolerant Coverage Control for an Autonomous Aerial Agent
• Probabilistically Robust Trajectory Planning of Multiple Aerial Agents