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针对传感器数据分析中代数模型方法存在的简化、丢失环境细节信息的问题,提出了一种用于移动机器人避障多次膨胀分析的激光雷达数据分析方法.该方法通过对激光测距数据进行多次不同程度的障碍边界膨胀,分析各膨胀图特征参数并提取局部环境形状特征,强化机器人局部环境认知及避障控制能力;膨胀系数组合在线选取和切换的灵活性特点使机器人可适应不同形状、尺寸的环境;机器人运动控制中引入环境形状特征参与机器人运动决策,增加了避碰控制以确保机器人在狭小环境下的安全.仿真对比验证了该方法在不同形状环境下的运动规划能力;实物实验验证了该方法可克服电机控制信号精度低、响应延时及胶轮打滑等不利因素影响,具有实际可行性.
Aiming at the problem of simplifying and losing the details of environment information in the algebraic model method of sensor data analysis, a data analysis method of lidar for obstacle avoidance multiple expansion analysis of mobile robot is proposed in this paper. Time varying degree of obstacle boundary expansion, analyzing the characteristic parameters of each expansion figure and extracting the shape features of the local environment, enhancing the robot’s local environment cognition and obstacle avoidance control ability; the flexibility characteristic of online selection and switching of the expansion coefficient combination enables the robot to adapt to different shapes , The size of the environment; the introduction of environmental characteristics of robot motion control robot involved in the decision-making of the movement, an increase of collision avoidance control to ensure the safety of the robot in a narrow environment. Simulation comparison and verification of the method in different shapes of environmental planning capabilities; physical Experiments show that this method can overcome the low precision of motor control signal, response delay and rubber wheel slip and other unfavorable factors, with practical feasibility.