自律飛行エージェントによる複数漂流者のモデル予測制御追跡
Model Predictive Control For Multiple Castaway Tracking with an Autonomous Aerial Agent
海上事故で漂流する複数の遭難者を、限られた視野の機載カメラを持つ自律UAVが追跡するためのモデル予測制御フレームワークを提案し、CNNによる検出確率の実験的評価とともに有効性を示した。
著者: Andreas Anastasiou, Savvas Papaioannou, Panayiotis Kolios, Christos G. Panayiotou
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
Over the past few years, a plethora of advancements in Unmanned Areal Vehicle (UAV) technology has paved the way for UAV-based search and rescue operations with transformative impact to the outcome of critical life-saving missions. This paper dives into the challenging task of multiple castaway tracking using an autonomous UAV agent. Leveraging on the computing power of the modern embedded devices, we propose a Model Predictive Control (MPC) framework for tracking multiple castaways assumed to drift afloat in the aftermath of a maritime accident. We consider a stationary radar sensor that is responsible for signaling the search mission by providing noisy measurements of each castaway's initial state. The UAV agent aims at detecting and tracking the moving targets with its equipped onboard camera sensor that has limited sensing range. In this work, we also experimentally determine the probability of target detection from real-world data by training and evaluating various Convolutional Neural Networks (CNNs). Extensive qualitative and quantitative evaluations demonstrate the performance of the proposed approach.
