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作 者:王敏 WANG Min(Shaanxi post and telecommunication college,Xianyang 712000,China)
出 处:《计算机测量与控制》2023年第5期160-165,173,共7页Computer Measurement &Control
摘 要:机器人运动过程中与外部障碍物之间容易发生碰撞,当碰撞作用力过大时会造成机器零件损坏的问题,为解决这一问题,设计基于AI深度学习的机器人碰撞预估计控制器;建立人机交互电路与串口通信电路,将伺服电机设备、运动控制器、PC感应装置分别接入既定作用区域内,完成预估计控制器的整体应用结构设计;以PyTorch深度学习框架为基础,定义激活函数,再根据预估计参数的实际取值范围,实现对目标机器人对象的精准检测。按照力矩控制条件表达式,确定碰撞行为的表现强度,完成对机器人运动路径的规划,联合相关应用设备,实现基于AI深度学习的机器人碰撞预估计控制器设计;实验结果表明,AI深度学习算法作用下,机器人与障碍物碰撞部位的接触面积不会超过0.25 m^(2),由碰撞行为导致的外部作用力相对较小,不会造成严重的机器零件损坏问题。Robots are prone to collide with external obstacles during movement.When a collision force is too large,machine parts will be damaged.to solve this problem,a robot collision pre-estimation controller based on ai depth learning is designed.The human-computer interaction circuit and serial communication circuit are established.The servo motor equipment,motion controller and PC induction device are respectively connected to the given action area to complete the overall application structure design of the pre-estimation controller.Based on the PyTorch depth learning framework,the activation function is defined,and then the accurate detection of the target robot object is realized by the actual value range of the pre-estimated parameters.According to the torque control condition expression,the performance strength of the collision behavior is determined,the robot motion path planning is completed,and the robot collision pre-estimation controller design based on artificial intelligence(AI)depth learning is realized by combining with the relevant application equipment.The experimental results show that the AI-based depth learning algorithm,the collision contact area between the robot and the obstacle will not exceed 0.25 m^(2),and the external force caused by the collision behavior is relatively small,which will not cause the machine parts serious damage.
关 键 词:AI深度学习 机器人碰撞 预估计控制器 人机交互 PC感应装置 PyTorch框架 激活函数
分 类 号:TP242[自动化与计算机技术—检测技术与自动化装置]
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