Robot-Relay: 学習型センサハンドオーバーネットワークによる建物全体のキャリブレーション不要ビジュアルサーボ
Robot-Relay : Building-Wide, Calibration-Less Visual Servoing with Learned Sensor Handover Network
カメラ間の位置・姿勢・距離のキャリブレーションを一切必要とせず、追跡スレッドでの同時ロボット検出から視点間のトポロジカルな接続を学習し、オフィス内の6台のカメラネットワークを介した自律移動を実現した。
著者: Luke Robinson, Matthew Gadd, Paul Newman, Daniele De Martini
分類: cs.RO
原文アブストラクト
We present a system which grows and manages a network of remote viewpoints during the natural installation cycle for a newly installed camera network or a newly deployed robot fleet. No explicit notion of camera position or orientation is required, neither global - i.e. relative to a building plan - nor local - i.e. relative to an interesting point in a room. Furthermore, no metric relationship between viewpoints is required. Instead, we leverage our prior work in effective remote control without extrinsic or intrinsic calibration and extend it to the multi-camera setting. In this, we memorise, from simultaneous robot detections in the tracker thread, soft pixel-wise topological connections between viewpoints. We demonstrate our system with repeated autonomous traversals of workspaces connected by a network of six cameras across a productive office environment.
