工程科学与技术2024，Vol.56Issue(1)：1-10,10.DOI:10.15961/j.jsuese.202201117
面向协作机器人的零力控制与碰撞检测方法研究
Research on Zero-force Control and Collision Detection for Cooperative Robots
摘要
Abstract
In the 3C(computer,communications,and consumer electronics)industry,there are strict requirements for robots'safety,interaction,accuracy,and flexibility.To solve the problem of compliant interactive control with cooperative robots,the zero-force control and collision detec-tion methods are studied in this paper.Firstly,a general inverse kinematics(Newton-MP)algorithm is established to analyze the redundant co-operative robots,in which the inverse kinematics problem is transformed into an iterative solution of the Newton-MP method.Secondly,for the zero-force control problem of cooperative robots,the friction force is considered to formulate a complete dynamic equation.Meanwhile,a com-plete dynamic equation is constructed based on the acceleration cubic friction model,in which the genetic algorithm is applied to identify multi-parameters of friction models.Furthermore,a collision detection method is proposed based on a One-class convolution neural network and an un-collision dataset is built to achieve the detection task.The pseudo-negative Gaussian data is incorporated into the One-class convolutional neural networks to optimize the feature space,and the binary cross-entropy loss serves as the loss function to train the network.The One-class convolu-tional neural network-based collision detection method has the ability to compensate the dynamic influence of model uncertainty,which solves the problem of inaccurate modeling of traditional collision detection methods.Finally,the experimental results demonstrate that the proposed New-ton-MP method achieves desired performance,i.e.,0.000 13 mm absolute error.In addition,compared with the ideal friction model,the velocity-fitted cubic friction model is a more preferred solution for zero force control.By analyzing the collision detection method of the external moment observer and the One-class convolution neural network,it can be proved that the One-class convolution neural network can accurately detect the abnormal collision of the cooperative robots in a model-free manner.关键词
动力学/协作机器人/One-class卷积神经网络/摩擦参数辨识Key words
dynamics/collaborative robot/One-class CNN/friction parameter identification分类
信息技术与安全科学引用本文复制引用
赵彬,吴成东,孙若怀,姜杨,吴兴茂..面向协作机器人的零力控制与碰撞检测方法研究[J].工程科学与技术,2024,56(1):1-10,10.基金项目
国家自然科学基金重点项目(U20A20197) （U20A20197）
辽宁省科技重大专项项目(2019JH1/10100005) （2019JH1/10100005）
辽宁省重点研发计划项目(2020JH2/10100040) （2020JH2/10100040）
