Efficient UAV Exploration with Hybrid Global�Local Strategy and Adaptive Yaw Planning
Yangyang Xue, Xiaotao Liu, Shaojian Zhou, Jingtai Ruan, Ting Huang
AI summary
Problem
Autonomous UAV exploration in complex environments is hindered by inefficient back-and-forth movements and redundant revisits caused by greedy local strategies and decoupled yaw planning.
Approach
The method dynamically switches between global frontier ordering and local clearance of isolated clusters, while using a reference yaw sequence with non-uniform B-spline adjustment to maximize sensor coverage in a single optimization.
Key results
- Dynamic mode switching eliminates redundant exploration of isolated frontier clusters
- Reference-guided yaw planning maximizes perception coverage via a single unified optimization
- Simulations demonstrate significant reductions in exploration time and distance versus state-of-the-art baselines
- Real-world experiments validate practical robustness and efficiency in complex environments
Why it matters
Offers a computationally efficient, plug-and-play framework that enhances UAV exploration performance for surveying, rescue, and 3D reconstruction tasks.
Abstract
Autonomous exploration in complex environments is frequently hindered by inefficient back-and-forth movements and repetitive revisits to previously explored areas. To address these drawbacks, we propose a two-mode hybrid dynamic exploration strategy that detects isolated frontier clusters and adaptively switches between two modes: global exploration mode (GEM) and local clearance mode (LCM). The GEM generates sequences for frontier exploration access, while the LCM employs a flight-time greedy approach to select and clear isolated clusters, thereby avoiding redundant visits. In addition, to achieve adaptive yaw planning, the proposed exploration strategy generates a reference yaw sequence based on the frontiers near the path trajectory. The reference yaw sequence is then used to perform yaw optimization, with non-uniform B- spline time adjustments ensuring feasible yaw trajectories, fully leveraging the UAV’s maneuverability and perception capabil- ities, and providing a plug-and-play solution for exploration research. Extensive simulations compared to state-of-the-art methods demonstrate that our approach significantly reduces both exploration time and distance, with real-world experiment confirming its practical effectiveness.