動的環境における障害物回避の難易度評価ベンチマーク
Evaluating Dynamic Environment Difficulty for Obstacle Avoidance Benchmarking
動的障害物回避の性能評価のため、障害物の数・大きさ・速度などを考慮した4つの難易度指標を提案し、150万回以上のシミュレーション実験で既存指標と比較検証した。
著者: Moji Shi, Gang Chen, Álvaro Serra Gómez, Siyuan Wu, Javier Alonso-Mora
分類: cs.RO
原文アブストラクト
Dynamic obstacle avoidance is a popular research topic for autonomous systems, such as micro aerial vehicles and service robots. Accurately evaluating the performance of dynamic obstacle avoidance methods necessitates the establishment of a metric to quantify the environment's difficulty, a crucial aspect that remains unexplored. In this paper, we propose four metrics to measure the difficulty of dynamic environments. These metrics aim to comprehensively capture the influence of obstacles' number, size, velocity, and other factors on the difficulty. We compare the proposed metrics with existing static environment difficulty metrics and validate them through over 1.5 million trials in a customized simulator. This simulator excludes the effects of perception and control errors and supports different motion and gaze planners for obstacle avoidance. The results indicate that the survivability metric outperforms and establishes a monotonic relationship between the success rate, with a Spearman's Rank Correlation Coefficient (SRCC) of over 0.9. Specifically, for every planner, lower survivability leads to a higher success rate. This metric not only facilitates fair and comprehensive benchmarking but also provides insights for refining collision avoidance methods, thereby furthering the evolution of autonomous systems in dynamic environments.
