文章摘要
江超,邢科新,林叶贵,张兴盛,张贵军.未知环境下移动机器人静态与动态实时避障方法研究[J].高技术通讯(中文),2019,29(10):1012~1020
未知环境下移动机器人静态与动态实时避障方法研究
Research on static and dynamic real-time obstacle avoidance methods for mobile robots in unknown environment
  
DOI:10.3772/j.issn.1002-0470.2019.10.009
中文关键词: 未知环境; 移动机器人; 避障; 自适应阈值; 相对坐标系
英文关键词: unknown environment, mobile robot, obstacle avoidance, adaptive threshold, relative coordinate
基金项目:
作者单位
江超  
邢科新  
林叶贵  
张兴盛  
张贵军  
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中文摘要:
      本文研究了场景地图未知的情况下,移动机器人运行至目标点过程中遇到的障碍物问题。针对移动机器人移动过程中遇到的静态障碍物的情况,本文提出一种自适应阈值的前沿目标点选取方法,得到局部目标点,从而有效地避开障碍物。针对移动机器人运动过程中遇到的动态障碍物的情况,首先,通过K mean聚类方法对激光雷达采集的障碍物信息进行聚类;其次,根据聚类得到的障碍物位置信息,采用最小二乘法拟合障碍物的运动学模型,并确定障碍物的运动速度与方向;再次,根据机器人的运动学模型与障碍物的运动学模型预测机器人与障碍物的碰撞情况;然后,考虑威胁距离和机器人自身尺寸对避障效果的影响,提出了一种改进的相对坐标系下的移动机器人避障策略。仿真和实验结果验证了所提方法的有效性和可行性。
英文摘要:
      In view of the obstacles encountered in the process of mobile robots to the target point in the case of unknown scene maps, in order to find the local target and avoid the static obstacles, an adaptive threshold method in selecting the frontier edge of local target is proposed. In view of dynamic obstacles, firstly, the K-mean clustering method is used to cluster the obstacle information collected by lidar. Secondly, based on least square method, the kinematic model of the dynamic obstacle is fitted by employing the data resulting from the K-means clustering method, then the speed and direction of dynamic obstacle are determined. Thirdly, the condition of collision between robot and obstacle is predicted by considering the kinematic model of robot and the kinematic model of the obstacle. Finally, an improved obstacle avoidance strategy based on relative coordinates is proposed by considering the threatening distance and the radius of robot. The simulation and experiment results verify the effectiveness and rapidity of the proposed method.
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