一种Delta机器人时间最优轨迹规划方法

摘要

In order to improve the Delta robot movement speed,a method of time-optimal trajectory planning is proposed with the combination of off-line optimization and online inquiry.Griding the working area on robot conveyor belt,it selects the center point of each grid as a standard,uses linear and circular interpolation in cartesian space for "door" type track to get the discrete location sequence,and calculates the discrete angle sequence in joint space through the inverse kinematics.It uses the particle swarm algorithm and gravitational search algorithm,based on fitness function of time optimal and under the premise of the joint velocity,acceleration,jerk continuous and smooth and constraints,constructs 7th order B-spline curve to get the off-line interpolation sequence of the angle-time in joint space.The optimal timing sequence is obtained by online query of 3D arrays.Experimental results show that the method is simple and easy.Delta robot in laboratory picks up object from the conveyor belt to the fixed position,and the time range is 0.6761s~0.7869s,so the method overcomes the shortcomings of low speeds of traditional planning method.%为提高Delta机器人的动作速度,提出一种离线寻优与在线查询相结合的时间最优轨迹规划方法.网格化机器人主传送带上的工作区域,选择每个网格中心点为标准点,在笛卡尔空间采用直线、圆弧插值获得门型轨迹的位置离散序列,经逆运动学计算出对应关节空间的角度离散序列.采用引力搜索的粒子群算法,以时间最优为适应度函数,在满足关节速度、加速度、脉动连续平滑及约束的条件下,构造7次B样条曲线,获取离线插值关节空间的角度-时间节点序列,并利用在线查询三维数组的方式获得最优时间节点序列.实验结果表明,该方法简单易行,以实验室Delta机器人为例,将主传送带上的物件抓取到固定位置,所用时间范围为0.6761s~0.7869s,克服了传统轨迹规划方法运动速度较慢的不足.