基于改进蚁群算法包装机器人轨迹规划研究

Research on trajectory planning of packaging robotbased on improved ant colony algorithm

针对六轴包装机器人在货物抓取到放入过程,由于路径规划时间长计算出的路径不准确导致机械臂在包装过程中的平稳性和重复精度不精确的问题,提出一种利用人工势场法和蚁群算法相结合的轨迹规划方法。通过将蚁群算法状态转移函数中加入人工势场合力,增加蚁群算法的初始值。基于MATLAB用D-H参数建立机器人模型,对改进后的算法进行仿真验证,对传统蚁群算法和改进蚁群算法分别在二维环境和三维环境中进行仿真验证,最后在真实环境下进行实验验证。结果表明,相较于传统算法改进后的算法具有较高的精度和稳定性,在搜索路径耗时、迭代次数和收敛速度等方面能够提高两倍以上。

Aiming at the problem that the six-axis packaging robot is in the process of grabbing and loading the goods,because the path calculated by the long path planning time is inaccurate and the mechanical arm is not accurate in the packaging process,the proposed and trajectory planning method combines artificial potential field and ant colony algorithm.The initial value of the ant colony algorithm is increased by adding the artificial potential force to the ant colony algorithm state transfer function.Based on MATLAB,the robot model is established by D-H parameters,and the improved algorithm is simulated and verified.The traditional ant colony algorithm and the improved ant colony algorithm are simulated and verified in 2D environment and 3D environment respectively.The results show that the improved algorithm has higher accuracy and stability than the traditional algorithm,and it is two times better in the search path time,iteration number and convergence speed.