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作 者:文郁 黄江帅 江涛 苏晓杰[1] WEN Yu;HUANG Jiang-shuai;JIANG Tao;SU Xiao-jie(School of Automation,Chongqing University,Chongqing 400044,China)
出 处:《控制与决策》2022年第8期2008-2016,共9页Control and Decision
基 金:国家重点研发计划项目(2019YFB1312002)。
摘 要:传统TEB(time elastic band)算法在杂乱场景下规划易出现倒退、大转向等异常行为,造成加速度跳变,控制指令不平滑,机器人受到大冲击,不利于移动机器人轨迹跟踪.鉴于此,提出一种改进TEB算法,通过增加危险惩罚因子约束规划更安全的运动轨迹,增加加速度跳变以抑制约束减小运动中的最大冲击,增加末端平滑约束以减小末端冲击,实现目标点平滑、准确到达.构建图优化问题,以机器人的位姿和时间间隔为节点、目标函数和约束函数为边,利用问题的稀疏性快速获得相应时刻点的控制量.最后,通过基于机器人操作系统的大量对比仿真测试以及真实差速机器人上的物理实验对提出的改进TEB算法进行性能验证.结果表明,改进TEB算法在复杂环境中能够规划出更安全、平滑的轨迹,减小机器人所受冲击,实现移动机器人更合理地运动.The traditional time elastic band(TEB) algorithm is prone to abnormal behaviors such as backsliding and large steering in the messy scene planning,which causes acceleration jumps,unsmooth control commands,and large impacts on robots,which is not conducive to the trajectory tracking of the mobile robot.This paper proposes an improved TEB algorithm,which can plan a safer motion trajectory by adding the hazard penalty factor constraint,reduce the maximum impact in motion by adding the acceleration jump suppression constraint,and reduce the end impact by adding the smooth ends constraint,so as to achieve the smooth and accurate arrival of the target point.Then a graph optimization problem is constructed.Taking the pose and time interval of the robot as the nodes,and the objective function and the constraint function as the edges,and the sparsity of the problem is used to quickly obtain the control amount at the corresponding time point.Finally,the performance of the proposed improved TEB algorithm is verified by a large number of comparison tests of robot operating system simulation and physical experiments of real differential robot planning algorithms.The results show that the improved TEB algorithm can plan safer and smoother trajectory in a complex environment,reduce the impact of the robot,and realize more reasonable movement of the robot.
关 键 词:时间弹性带算法 加速度跳变抑制 危险惩罚因子 末端平滑 移动机器人
分 类 号:TP273[自动化与计算机技术—检测技术与自动化装置]
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