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机构地区:[1]中国科学技术大学自动化系,安徽合肥230027
出 处:《机器人》2012年第4期476-484,共9页Robot
基 金:国家自然科学基金资助项目(61075073)
摘 要:针对移动机器人的环境建模问题,提出一种综合拓扑地图和儿何地图特点的混合环境模型——灰色定性地图.用凸剖分算法将环境中的自由空间分解为一组凸多边形.灰色定性地图的定性层由凸多边形及其之间的邻接关系构成,用于模拟人类在路径规划时的高层定性推理.定量层由凸多边形顶点的坐标和势场向量构成,用于决定机器人在连续空间中的运动方向和速度.理论分析和实验均表明:灰色定性地图可以模拟人类对环境认知的知识表达,并且可以仪由凸多边形邻接信息和顶点信息支持机器人完成路径规划且确保路径的平滑性,有效地降低了环境模型的空间复杂度.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 qual- itative 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 hu- man, and can support the robot complete path planning and ensure the smoothness of the path only by adjacency information and vertices information of convex polygons. The proposed method effectively reduces the space complexity of environment model.
分 类 号:TP24[自动化与计算机技术—检测技术与自动化装置]
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