距離センサと視覚慣性センサの融合による小型飛行ロボットの自己位置推定とナビゲーション
Range-Visual-Inertial Sensor Fusion for Micro Aerial Vehicle Localization and Navigation
UWB距離計測と視覚慣性オドメトリを2つの固定ラグスムーザで融合し、小型ドローンが混雑環境で高精度に自己位置推定・制御できる手法を提案。
著者: Abhishek Goudar, Wenda Zhao, Angela P. Schoellig
分類: cs.RO
原文アブストラクト
We propose a fixed-lag smoother-based sensor fusion architecture to leverage the complementary benefits of range-based sensors and visual-inertial odometry (VIO) for localization. We use two fixed-lag smoothers (FLS) to decouple accurate state estimation and high-rate pose generation for closed-loop control. The first FLS combines ultrawideband (UWB)-based range measurements and VIO to estimate the robot trajectory and any systematic biases that affect the range measurements in cluttered environments. The second FLS estimates smooth corrections to VIO to generate pose estimates at a high rate for online control. The proposed method is lightweight and can run on a computationally constrained micro-aerial vehicle (MAV). We validate our approach through closed-loop flight tests involving dynamic trajectories in multiple real-world cluttered indoor environments. Our method achieves decimeter-to-sub-decimeter-level positioning accuracy using off-the-shelf sensors and decimeter-level tracking accuracy with minimally-tuned open-source controllers.
