李书杰, 王鹏, 陈宗海. 一种移动机器人环境模型--灰色定性地图[J]. 机器人, 2012, 34(4): 476-484..
LI Shujie, WANG Peng, CHEN Zonghai. An Environment Model for Mobile Robot:Grey Qualitative Map. ROBOT, 2012, 34(4): 476-484..
Aiming at the environment modeling for mobile robot, a hybrid environment model including characteristics of both topological map and geometrical map is proposed, named grey qualitative model. The free space of environment is decomposed into a group of convex polygons by convex decomposition algorithm. The convex polygons and the adjacency relationship between them compose the qualitative level of grey qualitative map, which is used to simulate high-level qualitative reasoning for path planning of human. The quantitative level is composed of coordinates and potential field vectors of vertices of each convex polygon, which is used to determine the motion direction and speed of robot in continuous space. Theoretical analysis and experiments show that the grey qualitative map can simulate the expression of environment of human, and can support the robot complete path planning and ensure the smoothness of the path only by adjacency information and vertices infromantion of convex polygons. The proposed method effectively reduces the space complexity of environment model.
[1] 蔡自兴,邹小兵.移动机器人环境认知理论与技术的研究[J].机器人,2004,26(1): 87-91. Cai Z X, Zou X B. Research on environmental cognition theory and methodology for mobile robots[J]. Robot, 2004, 28(1): 87-91.
[2] Elfes A. Occupancy grids: A probabilistic framework for robot perception and navigation[D]. Pittsburgh, PA, USA: Carnegie Mellon University, 1989.
[3] Borges G A, Aldon M J. Robustified estimation algorithms for mobile robot localization based on geometrical environment maps[J]. Robotics and Autonomous Systems, 2003, 45(3/4): 131-159.
[4] Lisien B, Morales D, Silver D, et al. The hierarchical atlas[J]. IEEE Transactions on Robotics, 2005, 21(3): 473-481.
[5] Kuipers B. An intellectual history of the spatial semantic hierarchy[M]//Springer Transactions in Advanced Robotics, vol.38. Berlin, Germany: Springer-Verlag, 2008: 243-264.
[6] Kuipers B. The spatial semantic hierarchy[J]. Artificial Intelligence, 2000, 119(1/2): 191-233.
[7] Thrun S. Robotic mapping: A survey[J]. Computer and Information Science, 2002, 298(February): 1-35.
[8] 李天成,孙树栋,高扬.基于扇形栅格地图的移动机器人全局路径规划[J].机器人,2010,32(4): 547-552. Li T C, Sun S D, Gao Y. Fan-shaped grid based global path planning for mobile robot[J]. Robot, 2010, 32(4): 547-552.
[9] 刘作军,黄亚楼,王郸维.基于电路地图的移动机器人路径规划[J].机器人,2004,26(6): 563-568. Liu Z J, Huang Y L, Wang D W. Path planning of mobile robot based on circuit map[J]. Robot, 2004, 26(6): 563-568.
[10] Belta C, Isler V, Pappas G J. Discrete abstractions for robot motion planning and control in polygonal environments[J]. IEEE Transactions on Robotics, 2005, 21(5): 864-874.
[11] 李书杰,陈宗海.智能模拟中知识表达方法的综述与分析[C]//系统仿真技术及其应用.合肥:中国科学技术大学, 2009: 1-6. Li S J, Chen Z H. Survey and comments of knowledge representation in intelligent simulation research[C]//System Simulation Technology & Application. Hefei: University of Science and Technology of China, 2009: 1-6.
[12] Choi J, Choi M, Nam S Y, et al. Autonomous topological modeling of a home environment and topological localization using a sonar grid map[J]. Autonomous Robots, 2011, 30(4): 351-368.
[13] Deng J L. Control problems of grey system[J]. Systems & Control Letters, 1982, 1(5): 288-294.
[14] Zhou P D. An algorithm for partitioning polygons into convex parts[J]. Journal of Beijing Institute of Technology, 1997, 6(4): 363-368.
[15] Yan H Y, Wang H F, Chen Y Z. Mobile robot navigation in the triangulation of dynamic environment[C]//International Conference on Information and Automation. Piscataway, NJ, USA: IEEE, 2008: 776-783.