Title
Controlling a robotic stereo camera under image quantization noise
Abstract
AbstractIn this paper, we address the problem of controlling a mobile stereo camera under image quantization noise. Assuming that a pair of images of a set of targets is available, the camera moves through a sequence of Next-Best-Views NBVs, i.e. a sequence of views that minimizes the trace of the targets' cumulative state covariance, constructed using a realistic model of the stereo rig that captures image quantization noise and a Kalman Filter KF that fuses the observation history with new information.The proposed algorithm decomposes control into two stages: first the NBV is computed in the camera relative coordinates, and then the camera moves to realize this view in the fixed global coordinate frame. This decomposition allows the camera to drive to a new pose that effectively realizes the NBV in camera coordinates while satisfying Field-of-View constraints in global coordinates, a task that is particularly challenging using complex sensing models. We provide simulations and real experiments that illustrate the ability of the proposed mobile camera system to accurately localize sets of targets. We also propose a novel data-driven technique to characterize unmodeled uncertainty, such as calibration errors, at the pixel level and show that this method ensures stability of the KF.
Year
DOI
Venue
2017
10.1177/0278364917735163
Periodicals
Keywords
DocType
Volume
Range sensing, motion control, mapping
Journal
36
Issue
ISSN
Citations 
12
0278-3649
0
PageRank 
References 
Authors
0.34
22
5
Name
Order
Citations
PageRank
Charles Freundlich1182.32
Yan Zhang222.77
Alex Zihao Zhu3544.75
Philippos Mordohai4107658.86
Michael M. Zavlanos556149.72