针对室内环境下机器人的移动和定位需要，提出基于视觉FastSLAM的移动机器人自主探索方法.该方法综合考虑信息增益和路径距离，基于边界选取探索位置并规划路径，最化机器人的自主探索效，保探索任务的完整实现.在FastSLAM 2.0的基础上，利用视觉作为观测手段，有效融合全景扫描和地标跟踪方法，提高据观测效，并且引入地标视觉特征增强据关联估计，完成定位和地图绘制.实验表明，文方法能正选取最优探索位置并合理规划路径，完成探索任务，并且定位精度和地图绘制精度较高，鲁棒性较好.%To meet the requirement of the indoor travelling and the localization of mobile robot, an approach for autonomous exploration, localization and mapping is proposed based on visual FastSLAM. Firstly, exploration position based on frontiers of the explored region is selected with consideration of information gain and path distance, and then path planning with the shortest distance to exploration position is performed to ensure the maximized exploration efficiency and completeness of the task accomplishment. FastSLAM 2 . 0 is employed as the basis of the proposed localization and mapping algorithm obtaining observation data by using robot vision, data observation efficiency is increased by fusing panoramic scanning and landmark tracking, and data association estimation is improved by introducing landmark visual information into calculation. The experimental results show that the proposed approach selects the best exploration position accurately, makes path planning reasonably, and accomplishes the exploration task successfully. The localization and mapping results of the proposed algorithm are robust with high accuracy.
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