木構造に基づく3次元UAV探索のための次善軌道法
A Tree-based Next-best-trajectory Method for 3D UAV Exploration
未知で非構造的な環境において、情報利得の最大化と移動距離・ロボット動作の最小化を両立する、木構造ベースの統合探索・計画アルゴリズム（Exploration-RRT）を提案し、地下やGPS拒否環境での実機実験で有効性を示した。
著者: Björn Lindqvist, Akash Patel, Kalle Löfgren, George Nikolakopoulos
分類: cs.RO
原文アブストラクト
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.
