基于特征深度学习的机器人协调操作感知控制

为了在操作者与机器人之间实现更为稳定的负载运动状态,提出一种基于特征深度学习的机器人协调操作感知控制方法,分析机器人的协调操作原理,根据虚拟阻尼、虚拟惯量与虚拟刚度系数,构建人机协调操作模型,利用特征深度学习对模型内的神经网络进行网络信息的交互拓扑,优化机器人协调操作的感知性能.同时,减少内存占比,对人力交互信息滤波去...

Perceptual Control Simulation of Robot Coordinated Operation Based on Feature Deep Learning

In order to achieve a more stable load movement state between operator and robot,a perceptual control method for coordinated manipulation of robot based on feature depth learning was proposed.The principle of coordinated manipulation was analyzed.According to the virtual damping,virtual inertia and virtual stiffness coefficient,a coordinated manipulation model was constructed.The feature deep learning was adopted for the interactive topology of network information in neural network of model.The perception performance of coordinated manipulation of robot was optimized.Meanwhile,the proportion of memory was reduced,and then the human interaction information was filtered and denoised to further improve the operation stability.Moreover,the generalized damping,generalized inertia and generalized stiffness were integrated in the model to complete the perceptual control for coordinated manipulation of robot.Simulation results show that the proposed method has better accuracy of perceptual control,reduces the occupancy ratio of system resources,and improves the efficiency of perceptual control for coordinated operation.