FACT: ビジョンベースドローン群のための高速で能動的な座標初期化
FACT: Fast and Active Coordinate Initialization for Vision-based Drone Swarms
ステレオカメラとIMUのみを搭載したドローン群が、その場で回転しながら観測を行い、SDPとハンガリアン法で相対姿勢をリアルタイムに復元するシステムを提案した。
著者: Yuan Li, Anke Zhao, Yingjian Wang, Ziyi Xu, Xin Zhou, Jinni Zhou, Chao Xu, Fei Gao
分類: cs.RO
原文アブストラクト
Swarm robots have sparked remarkable developments across a range of fields. While it is necessary for various applications in swarm robots, a fast and robust coordinate initialization in vision-based drone swarms remains elusive. To this end, our paper proposes a complete system to recover a swarm's initial relative pose on platforms with size, weight, and power (SWaP) constraints. To overcome limited coverage of field-of-view (FoV), the drones rotate in place to obtain observations. To tackle the anonymous measurements, we formulate a non-convex rotation estimation problem and transform it into a semi-definite programming (SDP) problem, which can steadily obtain global optimal values. Then we utilize the Hungarian algorithm to recover relative translation and correspondences between observations and drone identities. To safely acquire complete observations, we actively search for positions and generate feasible trajectories to avoid collisions. To validate the practicability of our system, we conduct experiments on a vision-based drone swarm with only stereo cameras and inertial measurement units (IMUs) as sensors. The results demonstrate that the system can robustly get accurate relative poses in real time with limited onboard computation resources. The source code is released.
