ガウス確率場とガウス過程陰関数曲面を用いた能動的表面探査
Active Exploration Using Gaussian Random Fields and Gaussian Process Implicit Surfaces
視覚と触覚の計測を統合し、不確かな点群領域をロボットアームで触って効率的に3D表面を構築するオンライン確率フレームワークを提案した。物体検出や地形分類への応用も示した。
著者: Sergio Caccamo, Yasemin Bekiroglu, Carl Henrik Ek, Danica Kragic
分類: cs.RO
原文アブストラクト
In this work we study the problem of exploring surfaces and building compact 3D representations of the environment surrounding a robot through active perception. We propose an online probabilistic framework that merges visual and tactile measurements using Gaussian Random Field and Gaussian Process Implicit Surfaces. The system investigates incomplete point clouds in order to find a small set of regions of interest which are then physically explored with a robotic arm equipped with tactile sensors. We show experimental results obtained using a PrimeSense camera, a Kinova Jaco2 robotic arm and Optoforce sensors on different scenarios. We then demonstrate how to use the online framework for object detection and terrain classification.
