基于改进TEB算法的阿克曼移动机器人

Ackermann mobile robots based on improved TEB algorithm

目的:复杂环境中使用传统TEB算法进行导航时,会出现机器人与障碍物贴近运行或是与障碍物“抢位”,并且会出现突然的速度跳变,导致路径不平滑及震荡,给机器人带来碰撞的风险。针对以上问题,提出一种改进TEB算法。方法:首先,对障碍物边界进行膨胀处理,使机器人与障碍物保持安全距离。其次,在算法中加入加加速度约束以减少机器人在运动时的速度跳变,使规划的路径更加平滑。最后,在ROS中进行仿真实验并在阿克曼车体上对改进TEB算法进行实物测试。结果:实验表明改进TEB算法使机器人的震荡次数减少45.5%,线、角加加速度极差分别降低29.1%和31.2%。在复杂环境中算法规划出来的轨迹更加安全平滑且有效,较少机器人在导航过程中出现速度突变。结论:改进TEB算法适用于阿克曼机器人,使其更合理地运动。

Aims:When the traditional TEB algorithm is used for navigation in a complex environment,the robot will run close to the obstacle or“grab position”with the obstacle leading to the sudden acceleration and pumpy increasing the risk of collision.To solve these problems,an improved TEB algorithm is proposed.Methods:Firstly,the boundaries of obstacles were expanded to maintain a safe distance between the robot and the obstacles.Secondly,the acceleration constraint was added to the algorithm to reduce the speed jump of the robot during movement and smooth the planned path.Finally,the experiments were carried out in ROS to improve the TEB algorithm on the Ackermann car body.Results:Simulation results showed that the improved TEB algorithm could reduce the vibration number of the robot by 45.5%,and the range of line and angular acceleration by 13.1% and 31.2%.The trajectory planned by the algorithm in the complex environment was safer and smoother,and could effectively reduce the speed mutation of the robot during navigation.Conclusions:The improved TEB algorithm is suitable for the Ackermann robot to help it move more reasonably.