A Humanoid Robot Object Perception Approach Using Depth Images

Abstract

Humanoid robots have had significant research interest in the past two decades. Their classification as mobile manipulators allows them to work in unstructured environments creating new possibilities for human-robot interaction. Object grasping and manipulation are essential and enabling capabilities for mobile humanoid robots that require reliable perception. This paper presents a perception approach using depth images from an RGB-D camera to estimate the work plane and estimate object positions relative to the robot. Results from experiments with a set of object shapes and scenarios are presented.