基于多模型和改进WOA算法的Delta机器人柔性夹持器抓取方法研究

Research on the grasping method of delta robot flexible gripper based on multiple models and improved WOA algorithm

[目的]解决Delta机器人柔性夹持器抓取方法存在的控制精度和适应性较差等问题。[方法]以Delta机器人柔性夹持器为研究对象,提出一种多模型和改进鲸鱼算法相结合的Delta机器人柔性夹持器抓取方法。建立稳定抓取优化模型,在抓持对象表面寻求最佳接触位置。建立无损抓取优化模型,在确保稳定抓起物体的前提下使接触力尽可能地小。结合粒子群算法和鲸鱼算法求解模型。通过试验验证了所提抓取方法的优越性。[结果]所提方法不仅具有良好的控制精度,还能够适应不同形状和大小的物体,具有较高的灵活性和适应性,抓取成功率>96%,抓取损伤率为0。[结论]所提方法有效提高了Delta机器人柔性夹持器抓取方法的性能,适用于果蔬和易碎物品的分拣工作。

[Objective]Solve the problems of poor control accuracy and adaptability in the Delta robot flexible gripper grasping method.[Methods]This article took the Delta robot flexible gripper as the research object and proposed a Delta robot flexible gripper grasping method that combined multiple models and improved whale algorithm.Established a stable grasping optimization model to seek the optimal contact position on the surface of the grasping object.Established a non-destructive grasping optimization model to minimize contact force while ensuring stable grasping of objects.Combine particle swarm optimization algorithm and whale algorithm to solve the model.The superiority of the proposed grasping method had been verified through experiments.[Results]The proposed method not only had good control accuracy,but also could adapt to objects of different shapes and sizes,with high flexibility and adaptability,success rate of grasping was greater than 96%,grasping damage rate was 0.[Conclusion]The proposed method effectively improves the performance of the Delta robot flexible gripper gripping method and is suitable for sorting fruits,vegetables,and fragile items.