Abstract：Aiming at robot special service tasks and man-machine interaction in a home environment, a semantic room map of semi-unknown environment is built using QR code based self-similar artificial object mark plastered on large objects. First, a topology map with the function of room segmentation is built based on spectral clustering algorithms. Then object information database and adscription relationship map are set up based on object information stored in the QR code. Finally, a semantic map including object information description, room functional information and attributive relation between room and object is formed, which gives complete and anthropopathic information for object location, object management and robotic service in a home environment. The simulation results show that the service robot using semantic map can understand human semantic statement, produce reasonable service path and achieve function-driving navigation.
[1] Nüchter A, Hertzberg J. Towards Semantic Maps for Mobile Robots. Robotics and Autonomous System, 2008, 56(11): 915-926 [2] Wolf D F, Sukhatme G S. Semantic Mapping Using Mobile Robots.
IEEE Trans on Robotics, 2008, 24(2): 245-258 [3] Rusu R B, Marton Z C, Blodow N, et al. Towards 3D Point Cloud Based Object Maps for Household Environments. Robotics and Autonomous Systems, 2008, 56(11): 927-941 [4] Grisetti G, Stachniss C, Burgard W. Improved Techniques for Grid Mapping with Rao-Blackwellized Particle Filters. IEEE Trans on Robotics, 2007, 23(1): 34-46 [5] Stachniss C, Burgard W. Mapping and Exploration with Mobile Robots Using Coverage Maps // Proc of the IEEE/RSJ International Conference on Intelligent Robots and Systems. Las Vegas, USA, 2003: 467-472 [6] van Zwynsvoorde D, Simeon T, Alami R. Incremental Topological Modeling Using Local Voronoi-Like Graphs // Proc of the IEEE International Conference on Intelligent Robots and Systems. San Francisco, USA, 2000: 897-902 [7] Beeson P, Jong N K, Kuipers B. Towards Autonomous Topological Place Detection Using the Extended Voronoi Graph // Proc of the IEEE International Conference on Robotics and Automation. Barcelona, Spain, 2005: 4373-4379 [8] Blanco J L, Gonz′alez J, Fern′andez-Madrigal J A. Subjective Local Maps for Hybrid Metric-Topological SLAM. Robotics and Autonomous Systems, 2009, 57(1): 64-74 [9] Blanco J L, Fernández-Madrigal J A, González J. Toward a Unified Bayesian Approach to Hybrid Metric-Topological SLAM. IEEE Trans on Robotics, 2008, 24(2): 259-270 [10] Krse B J A, Vlassis N, Bunschoten R, et al. A Probabilistic Model for Appearance-Based Robot Localization. Image and Vision Computing, 2001, 19(6): 381-391 [11] Wooden D. A Guide to Vision-Based Map Building. Robotics Automation, 2006, 13(6): 94-98 [12] Masahiro T. Robust 3D SLAM with a Stereo Camera Based on an Edge-Point ICP Algorithm // Proc of the IEEE International Conference on Robotics and Automation. Kobe, Japan, 2009: 2205-2210 [13] Ogawa Y, Shimada N, Shirai Y. Environmental Mapping for Mobile Robot by Tracking SIFT Feature Points Using Trinocular Vision // Proc of SICE Annual Conference. Takamatsu, Japan, 2007: 1996-2001 [14] Murali V N, Birchfield S T. Autonomous Navigation and Mapping Using Monocular Low-Resolution Grayscale Vision // Proc of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Anchorage, USA, 2008: 1-8 [15] Zhao Shoupeng, Tian Guohui, Li Xiaolei. Robot Autonomous Localization Based on a Single Artificial Landmark. Journal of Shandong University: Engineering Science, 2007, 37(4): 39-45 (in Chinese) (赵守鹏,田国会,李晓磊.基于单个人工地标的机器人自主定位.山东大学学报:工学版, 2007, 37(4): 39-45) [16] Xue Hongtao, Tian Guohui, Li Xiaolei, et al, Application of the QR Code for Various Object Identification and Manipulation. Journal of Shandong University: Engineering Science, 2007, 37(6): 25-31 (in Chinese) (穴洪涛,田国会,李晓磊,等.QR Code 在多种类物体识别与操作中的应用.山东大学学报:工学版, 2007, 37(6): 25-31) [17] Ng A, Jordan M, Weiss Y. On Spectral Clustering: Analysis and an Algorithm // Dietterich T G, Becker S, Ghahramani Z, eds. Advances in Neural Information Processing Systems. Cambridge, USA: MIT Press, 2001, XIV: 345-352 [18] Scharstein D, Briggs A J. Real-Time Recognition of Self-Similar Landmarks. Image and Vision Computing, 2001, 19(11): 763-772 [19] Si Bingyu. Research on the Problem Concerning Visual Artificial Landmark Based Navigation of Autonomous Mobile Robot. Ph.D Dissertation. Shenyang, China: Northeast University. College of Information Science and Engineering, 2003 (in Chinese) (司秉玉.基于可视人工路标的自主机器人导航若干问题研究.博士学位论文.沈阳:东北大学.信息科学与工程学院, 2003) [20] Becker C, Salas J, Tokusei K. Reliable Navigation Using Landmarks // Proc of the IEEE International Conference on Robotics and Automation. Montreal, Canada, 1995: 401-406 [21] Taylor C J, Kriegman D J. Vision-Based Motion Planning and Exploration Algorithms for Mobile Robots. IEEE Trans on Robotics and Automation, 1998, 14(3): 417-426 [22] Yu Zhong, Xu Wenli, Chen Feng. Two-Step Method for Detection of Circle Profiles in Edge Images. Journal of Computer-Aided Design Computer Graphics, 2005, 17(2): 243-246 (in Chinese) (于 中,徐文立,陈 峰.边缘图像中圆形轮廓的两步法检测.计算机辅助设计与图形学学报, 2005, 17(2): 243-246)
2010, Vol. 23 
