A Tree-based Next-best-trajectory Method for 3D UAV Exploration
<|reference_start|>A Tree-based Next-best-trajectory Method for 3D UAV Exploration: This work presents a fully integrated tree-based combined exploration-planning algorithm: Exploration-RRT (ERRT). The algorithm is focused on providing real-time solutions for local exploration in a fully unknown and unstructured environment while directly incorporating exploratory behavior, robot-safe path planning, and robot actuation into the central problem. ERRT provides a complete sampling and tree-based solution for evaluating "where to go next" by considering a trade-off between maximizing information gain, and minimizing the distances travelled and the robot actuation along the path. The complete scheme is evaluated in extensive simulations, comparisons, as well as real-world field experiments in constrained and narrow subterranean and GPS-denied environments. The framework is fully ROS-integrated, straight-forward to use, and we open-source it at https://github.com/LTU-RAI/ExplorationRRT.<|reference_end|>
@article{lindqvist2024a,
    title={A Tree-based Next-best-trajectory Method for 3D UAV Exploration},
    author={Bj"orn Lindqvist, Akash Patel, Kalle L"ofgren, George Nikolakopoulos},
    journal={arXiv preprint arXiv:2407.04386},
    year={2024},
    doi={10.1109/TRO.2024.3422052},
    archivePrefix={arXiv},
    eprint={2407.04386},
    primaryClass={cs.RO}
}