ARENA: 複数目的の3Dインフラ点検を行うUAVのための適応的リスク認識・省エネナビゲーション
ARENA: Adaptive Risk-aware and Energy-efficient NAvigation for Multi-Objective 3D Infrastructure Inspection with a UAV
UAVによる3Dインフラ点検で、安全性・時間・エネルギーを同時に最適化し、リスク変化に応じて軌道をオンライン適応させるマルチ目的経路計画手法を提案した。
著者: David-Alexandre Poissant, Alexis Lussier Desbiens, François Ferland, Louis Petit
分類: cs.RO
原文アブストラクト
Autonomous robotic inspection missions require balancing multiple conflicting objectives while navigating near costly obstacles. Current multi-objective path planning (MOPP) methods struggle to adapt to evolving risks like localization errors, weather, battery state, and communication issues. This letter presents an Adaptive Risk-aware and Energy-efficient NAvigation (ARENA) MOPP approach for UAVs in complex 3D environments. Our method enables online trajectory adaptation by optimizing safety, time, and energy using 4D NURBS representation and a genetic-based algorithm to generate the Pareto front. A novel risk-aware voting algorithm ensures adaptivity. Simulations and real-world tests demonstrate the planner's ability to produce diverse, optimized trajectories covering 95% or more of the range defined by single-objective benchmarks and its ability to estimate power consumption with a mean error representing 14% of the full power range. The ARENA framework enhances UAV autonomy and reliability in critical, evolving 3D missions.
