Title: Interactive indoor environment mapping through visual tracking of human skeleton

Authors: Cheng Zhao; Wei Pan; Huosheng Hu

Addresses: Cognitive Science Department, Fujian Key Laboratory of the Brain-like Intelligent Systems, Xiamen University, Xiamen 361005, China ' Cognitive Science Department, Fujian Key Laboratory of the Brain-like Intelligent Systems, Xiamen University, Xiamen 361005, China ' School of Computer Science and Electronic Engineering, University of Essex, Colchester CO4 3SQ, UK

Abstract: This paper presents a novel human-robot interaction approach to grid mapping of an indoor environment based on a 3D kinect sensor and the grid-based mapping algorithm. It mainly includes three modules: skeleton tracking, robot control and GMapping. Firstly, the skeleton tracking module builds a human skeleton model, extracts the skeleton joints' position information from 3D visual data and generates digital signals through identifying some simple motions and events. Then according to different digital signals and joints' position information, the robot control module enables the robot to take different actions such as following the person, stop and so on. Finally, the grid map of the environment is built through GMapping algorithm based on odometry and laser data, which is improved by Rao-Blackwellised particle filters. The proposed approach has been implemented successfully in several different buildings and can be applied to service robots. Compared with traditional roaming for mapping, human guiding the robot for mapping is more efficient and takes less time in a complicated environment. Meanwhile, compared with wearable motion sensors attached to the human body, this approach is more convenient and make the user more comfortable.

Keywords: skeleton tracking; human-robot interaction; HRI; interactive mapping; indoor environment; grid mapping; visual tracking; human skeleton; robot control; skeleton modelling; joint positioning; particle filters; service robots; mobile robots; human guided mapping; kinect sensors; odometry; laser data.

DOI: 10.1504/IJMIC.2013.057565

International Journal of Modelling, Identification and Control, 2013 Vol.20 No.4, pp.319 - 328

Available online: 13 Nov 2013 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article