基于混合环境模型的自主移动机器人环境探索研究

摘要

For exploring the interior unknown environment,by using an autonomous mobile robot this paper proposes a high-effect autonomous environment exploration algorithm based on a hybrid topological-metric map.The topological map based on environment Opening-Points is built in real-time according to current sensor information.The optimal instant target is selected as the exploration direction for the next step by analyzing and dealing with the OpeningPoints.In the framework of Rao-Blackwellized particle filter (RBPF),the grid map based Simultaneous Localization and Mapping (SLAM) is introduced into the autonomous exploration process of the mobile robot,which provides the accurate position estimate to improve the position accuracy of the topological node effectively and complete the exploration task smoothly.The exploration algorithm based on the above two strategies gives consideration to both accuracy and efficiency.The validity and practicability of the proposed exploration approach was validated by a lot of experiments on the mobile robot Pioneer3-DX.%针对未知室内环境,提出了一种基于度量-拓扑混合式地图的高效的自主移动机器人环境探索策略:移动机器人根据当前传感器数据实时构建环境通路点拓扑地图,对各个环境通路点进行细致分析与处理,选择最优的即时目标点作为规划的探索方向；在Rao-Blackwellized粒子滤波(RBPF)框架下,将基于栅格地图的同步定位与地图创建(SLAM)算法引入到机器人自主探索任务中,提供准确的机器人位姿估计,以有效改善拓扑节点的位置精度,保证机器人顺利完成探索任务.基于上述策略提出的环境探索算法能够兼顾探索效率与精度.通过在配有激光测距仪的Pioneer3-DX型移动机器人平台上进行现场实验,有力验证了这种探索算法的有效性及实用性.