基于智能空间的服务机器人导航若干关键问题研究
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摘要
机器人在结构复杂、区域性特征明显的环境中(如家庭环境)执行服务任务首要解决的问题是在该环境中的导航。传统的机器人导航中构建的地图侧重于空间几何结构表示,未考虑机器人服务环境的区域性特征。智能空间技术的引入提高了服务机器人感知环境的能力。本文基于智能空间技术,围绕家庭环境下适合机器人服务任务执行的地图构建及导航,室外大范围环境下的导航开展了如下研究工作。
针对家庭环境中各房间功能、布局不一等特点,基于智能空间中的人工地标设计了地图构建模型。模型将环境划分为全局层和局部层。全局层地图可实现机器人起始位置和目标位置所在房间的确定及不同房间之间的路径搜寻；局部层地图用于单个房间内机器人由当前位置运动到目标位置或房间门口位置。针对各层地图模型构建的需要,设计了人工地标信息存储格式,生成了全局层地图数据库和各房间连通关系数据库。
针对大范围半未知环境下机器人的导航进行了研究,提出了分布式导航信息获取模式。摆脱了传统的地图构建-全局定位-路径规划的导航模式。该模式将环境划分为全局引导层和局部搜寻层,机器人通过识读贴放于道路拐角处的全局引导层人工地标获得目标点所在局部区域信息及如何到达该区域的引导信息,通过识读局部搜寻层人工地标获知各目标点的邻接关系信息,并最终寻找到本次导航任务的目标点。
对实验室现有的顶棚投影器辅助导航系统进行了系统研究,指出了存在的不足之处,如光斑速度不可调,光斑无法实现匀速运动等。基于现有辅助导航系统,设计了激光投影循迹系统,实现了服务器与投影器和机器人之间的实时通讯,通过服务器端程序可进行光斑速度的设定,及投影器云台的手动控制。设计了机器人光斑跟踪算法。通过实验验证了激光投影循迹系统的有效性。
The primary problem to be solved while robots perform service tasks in the environment which own complex structure and obvious regional characteristics is navigation. Map built in the traditional robot navigation focuses on the geometry of space, without considering of the regional characteristics of the robot service environment. The introduction of the intelligent space technology improves the ability of service robot to perceive the environment. Based on intelligent space technology, map building and navigation for the implementation of service tasks in home environment, navigation under a wide range of outdoor surrounding are carried out in this paper.
Features for the difference of room function and layout, the map building model based on the artificial landmark in the intelligent space is designed in this paper. The model divides the environment into global and local layer. Map of the global layer is to determine which room the starting position and the target position belong to, and search path among difference apartments. Map of the local layer is to ensure the robot to move to the goal position or the door from current location in the single room. For the map building needs of each layer, information storage format of the artificial landmark is designed, mean while the global level map database and the connectivity relationship database of each room are generated.
In this thesis, the research of navigation in wide range semi-unknown environment is covered, and distributed navigation information acquisition mode is proposed. Traditional navigation mode of map building、global locating、path planning is been gotten rid. The mode divides the environment into global guiding layer and the local searching layer. Robot informs the guiding information of which local area the target point belongs to and how to reach this region by reading the global level artificial landmark attached around the corner. Adjacency information of destination points is obtained by the robot on reading the local searching level artificial landmark, and finally the target position of the navigation task is found by the robot.
The existing ceiling projector based accessory navigation system has been systematically learned by the author. The inadequate such as the non-adjustability of the spot rate and uniform motion cannot be achieved of the spot has been pointed out. Laser projecting and tracking system is designed based on the available accessory navigation system. The real-time communication between the server and projector、the server and robot is realized in this paper. The spot rate can be set by the sever-side program, and the manual control mode of projector linkage is achieved. Spot tracking algorithm is designed in the thesis. The effectiveness of laser projecting and tracking system is verified by experiments.
针对家庭环境中各房间功能、布局不一等特点,基于智能空间中的人工地标设计了地图构建模型。模型将环境划分为全局层和局部层。全局层地图可实现机器人起始位置和目标位置所在房间的确定及不同房间之间的路径搜寻；局部层地图用于单个房间内机器人由当前位置运动到目标位置或房间门口位置。针对各层地图模型构建的需要,设计了人工地标信息存储格式,生成了全局层地图数据库和各房间连通关系数据库。
针对大范围半未知环境下机器人的导航进行了研究,提出了分布式导航信息获取模式。摆脱了传统的地图构建-全局定位-路径规划的导航模式。该模式将环境划分为全局引导层和局部搜寻层,机器人通过识读贴放于道路拐角处的全局引导层人工地标获得目标点所在局部区域信息及如何到达该区域的引导信息,通过识读局部搜寻层人工地标获知各目标点的邻接关系信息,并最终寻找到本次导航任务的目标点。
对实验室现有的顶棚投影器辅助导航系统进行了系统研究,指出了存在的不足之处,如光斑速度不可调,光斑无法实现匀速运动等。基于现有辅助导航系统,设计了激光投影循迹系统,实现了服务器与投影器和机器人之间的实时通讯,通过服务器端程序可进行光斑速度的设定,及投影器云台的手动控制。设计了机器人光斑跟踪算法。通过实验验证了激光投影循迹系统的有效性。
The primary problem to be solved while robots perform service tasks in the environment which own complex structure and obvious regional characteristics is navigation. Map built in the traditional robot navigation focuses on the geometry of space, without considering of the regional characteristics of the robot service environment. The introduction of the intelligent space technology improves the ability of service robot to perceive the environment. Based on intelligent space technology, map building and navigation for the implementation of service tasks in home environment, navigation under a wide range of outdoor surrounding are carried out in this paper.
Features for the difference of room function and layout, the map building model based on the artificial landmark in the intelligent space is designed in this paper. The model divides the environment into global and local layer. Map of the global layer is to determine which room the starting position and the target position belong to, and search path among difference apartments. Map of the local layer is to ensure the robot to move to the goal position or the door from current location in the single room. For the map building needs of each layer, information storage format of the artificial landmark is designed, mean while the global level map database and the connectivity relationship database of each room are generated.
In this thesis, the research of navigation in wide range semi-unknown environment is covered, and distributed navigation information acquisition mode is proposed. Traditional navigation mode of map building、global locating、path planning is been gotten rid. The mode divides the environment into global guiding layer and the local searching layer. Robot informs the guiding information of which local area the target point belongs to and how to reach this region by reading the global level artificial landmark attached around the corner. Adjacency information of destination points is obtained by the robot on reading the local searching level artificial landmark, and finally the target position of the navigation task is found by the robot.
The existing ceiling projector based accessory navigation system has been systematically learned by the author. The inadequate such as the non-adjustability of the spot rate and uniform motion cannot be achieved of the spot has been pointed out. Laser projecting and tracking system is designed based on the available accessory navigation system. The real-time communication between the server and projector、the server and robot is realized in this paper. The spot rate can be set by the sever-side program, and the manual control mode of projector linkage is achieved. Spot tracking algorithm is designed in the thesis. The effectiveness of laser projecting and tracking system is verified by experiments.
引文
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[3]田国会,李晓磊.家庭服务机器人智能空间技术研究与进展[J].山东大学学报：工学版,2007,37(5)：53-59.
[4]Jinwoo Choi, Sunghwan Ahn, Wan Kyun Chung. Robust sonar feature detection for the SLAM of mobile robot[C]//Proceedings of IEEE International Conference on Intelligent Robots and Systems.Alberta,Canada: IEEE Press, 2005:3415-3420.
[5]Sukhan Lee,Seongsoo Lee. Recursive particle filter with geometric constraints for SLAM[C]//Proceedings of IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems. Heidelberg,Germany:IEEE Press,2006:395-401.
[6]王志文,郭戈.移动机器人导航技术现状及展望[J].机器人,2003,25(5)：470-474.
[7]Fang Fang, Xudong Ma, Xianzhong Dai. A multi-sensor fusion SLAM approach for mobile robots[C]// Proceedings of IEEE International Conference on Mechatronics and Automa-tion.Niagara Falls,Canada:IEEE Press,2005:1837-1841.
[8]丁伟,孙华,曾建辉.基于多传感器信息融合的移动机器人导航综述[J].传感器与微系统,2006,25(7)：1-3.
[9]A. Tapus, R. Siegwart, Incremental robot mapping with fingerprints of places, in: Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, IROS,2005, pp.2429-2434.
[10]Quijano, Humberto J., Garrido, Leonardo. Improving Cooperative Robot Exploration Using an Hexagonal World Representation, Electronics, Robotics and Automotive Mechanics Conference,2007. CERMA 2007,25-28 Sept.2007 Page(s):450-455
[11]Motard, E.; Raducanu, B.; Cadenat, V.; Vitria, J.; Incremental On-Line Topological Map Learning for A Visual Homing Application, Robotics and Automation,2007 IEEE International Conference on,10-14 April 2007 Page(s):2049-2054
[12]Boada, B.L.; Castejon, C.; Moreno, L.;Topo-geometric modeling and localization in indoor environments, IECON 02 [Industrial Electronics Society, IEEE 2002 28th Annual Conference of the], Volume 4,5-8 Nov.2002 Page(s):2587-2592 vol.4
[13]Byung Jae Park; Se-Jin Lee; Jong-Hwan Lim; Dong-Woo Cho; Angular Uncertainty Reduction of Sonar Range Data for a Grid-based Map Building, SICE-ICASE,2006. International Joint Conference, Oct.2006 Page(s):2010-2014
[14]S. Thrun, "Learning metric-topological maps for indoor mobile robot navigation", Artificial Intelligence, Volume 99, Issue 1, February 1998, Pages 21-71.
[15]N. Tomatis, I. Nourbakhsh and R. Siegwart, "Hybrid Simultaneous Localization and Map Building:A Natural Integration of Topological and Metric", Robotics and Autonomous Systems,44,3-14., July 2003.
[16]A. Martinelli, A. Tapus, K.O. Arras and R. Siegwart, "Multi-resolution SLAM for Real World Navigation", In Proceedings of the 11th International Symposium of Robotics Research, Siena, Italy,2003.
[17]王珂,王伟,庄严,孙传昱,基于几何—拓扑广域三维地图和全向视觉的移动机器人自定位,自动化学报,2008,34(11)：1369-1378
[18]Sangwoo Jo, Qonita M. Shahab, Yong-Moo Kwon, Sang Chul Ahn, Indoor Modeling for Interactive Robot Service, SICE-ICASE International Joint Conference 2006 in Bexco, Busan, Korea,2006,10:3531-3536
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