動的環境におけるMAV向けロバスト視覚ベース障害物回避
Robust Vision-based Obstacle Avoidance for Micro Aerial Vehicles in Dynamic Environments
ステレオカメラの深度画像ペアから移動障害物を検出・追跡し、確率制約付きモデル予測制御で衝突確率を抑えながら回避するオンボード手法を提案し、実機で検証した。
著者: Jiahao Lin, Hai Zhu, Javier Alonso-Mora
分類: cs.RO
原文アブストラクト
In this paper, we present an on-board vision-based approach for avoidance of moving obstacles in dynamic environments. Our approach relies on an efficient obstacle detection and tracking algorithm based on depth image pairs, which provides the estimated position, velocity and size of the obstacles. Robust collision avoidance is achieved by formulating a chance-constrained model predictive controller (CC-MPC) to ensure that the collision probability between the micro aerial vehicle (MAV) and each moving obstacle is below a specified threshold. The method takes into account MAV dynamics, state estimation and obstacle sensing uncertainties. The proposed approach is implemented on a quadrotor equipped with a stereo camera and is tested in a variety of environments, showing effective on-line collision avoidance of moving obstacles.
