项目名称: 面向野外服务的轮式机器人运动规划与地图构建研究
项目编号: No.51275405
项目类型: 面上项目
立项/批准年度: 2013
项目学科: 机械、仪表工业
项目作者: 弋英民
作者单位: 西安理工大学
项目金额: 85万元
中文摘要: 机器人运动规划与地图构建在无GPS的坑道、矿井、星际车以及GPS失效的智能车自主导航具有巨大的发展潜力和应用前景。现有研究成果在野外未知环境下机器人不具有自主学习特性,计算的理论框架算法复杂,地图只适合静态地图和一般动态地图,因此不能直接采用。针对野外环境的未知参数特性,提出野外环境下机器人运动规划与地图构建的对偶控制方法。提出一种随机移动目标的主动学习方法和机器人非完整系统的避障规划方法,通过边学习边控制的对偶控制思想,解决野外未知环境下的机器人运动规划问题。针对野外环境的大数据量计算问题,提出泛图层的低计算复杂度的机器人避障规划方法。针对随机移动目标的动态特性,提出带时间维地图的构建方法,解决动态地图和静态地图的联合数据关联问题。最终解决野外未知环境下机器人运动规划与地图构建的相关关键问题。
中文关键词: 野外未知环境;轮式机器人;运动规划;地图构建;
英文摘要: Robot motion planning and mapping in wild unknown environment has great potential for development and application prospects in the trenches without GPS, mine, interplanetary vehicles and GPS failure intelligent vehicle autonomous navigation. Existing research can not be directly used for the robot does not have a self-learning characteristics, the complexity of the theoretical framework algorithm, the map is only suitable for static maps and dynamic maps in the wild unknown environment. For the unknown parameters characteristic in the wild environment, the dual control method of robot motion planning in the field environment and mapping is proposed. An active learning method on stochastic moving target and robot obstacle avoidance and planning methods on nonholonomic systems are proposed. Through the dual control method with learning and control, the robot motion planning in the wild unknown environment will be solved. For the calculation of the large amount of data in the wild environment, the low computational complexity of the robot obstacle avoidance planning method with wide layers is proposed. For the dynamic characteristics of the randomly moving target, the four-dimension map with a time dimension is proposed to solve the joint data association problem of dynamic maps and static maps. As results, the key
英文关键词: wild unknown environments;wheeled robot;motion planning;map building;