Position Uncertainty Reduction of Mobile Robot Based on DINDs in Intelligent Space

Abstract

This paper proposes a localization of mobile robot using the images by distributed intelligent networked devices (DINDs) in intelligent space (ISpace). This scheme combines data from the observed position using dead-reckoning sensors and the estimated position using images of moving object, such as those of a walking human, used to determine the moving location of a mobile robot. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the intelligent space. Using the a-priori known path of a moving object and a perspective camera model, the geometric constraint equations that represent the relation between image frame coordinates of a moving object and the estimated position of the robot are derived. The proposed approach is applied for a mobile robot in ISpace to show the reduction of uncertainty in the determining of the location of the mobile robot.