Relative Position Algorithm for Optimal Camera Placement of Large Scale Volume Localization System

Abstract

Large Scale Volume Localization System (LSVLS) with camera network has appropriate precise and cost, which is a promising system in metrology and localization in industry and lives. Optimal camera placement is significant to lower cost and facilitate target’s auto-control for mobile robot in the large workspace. The author proposed a relative position algorithm (RPA) to find optimal camera placement of dozens even hundreds cameras. RPA calculated the minimum cameras and the coordinate and posture of each camera, after figured out the best posture of the camera in camera placement area. The result of optimal camera placement can enhance greatly the efficiency of camera placement in LSVLS and is verified with a model of a mobile robot works in a laboratory.