动态环境下基于路径规划的机器人同步定位与地图构建

Robot Simultaneous Localization and Mapping Based on Path Planning in Dynamic Environments

针对动态环境下随机目标同时为特征点和障碍物的情况,提出一种基于路径规划的同步定位与地图构建(SLAM)算法.机器人在同步定位与地图构建的同时,基于势场原理来规划机器人下一步的运动控制规律.利用混合当前统计模型的交互式多模型(IMM)方法预测随机目标的轨迹,采用最近邻数据关联方法将动态随机目标关联到地图中.算法构建的地图由静态特征点和随机目标的轨迹组成.仿真结果表明,提出的算法解决了动态环境中存在的随机目标同时为障碍物时机器人的同步定位与地图构建问题,相关性能指标验证了算法的一致性估计.

To deal with random object characterized by both landmark and obstacle in dynamic environments, a simultaneous localization and mapping （SLAM） algorithm based on path planning is presented. During robot simultaneous localization and mapping, the robot motion control law is planned for the next step based on the potential field theory. The trajectory of random object is predicted by the interacting multiple model （IMM） method of hybrid current statistical model. The dynamic random object is associated with the map by the nearest neighbor method. The built map by the proposed algorithm is comprised of trajectories of static landmarks and random objects. Simulation results show that the SLAM problem in dynamic environments with random objects characterized by obstacle is solved by the proposed algorithm. The relevant performance indicators prove that the estimation of the algorithm is consistent.