首页> 外文会议>IEEE Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems >Sensorless External Force Detection Method for Humanoid Robot Arm based on BP Neural Network
【24h】

Sensorless External Force Detection Method for Humanoid Robot Arm based on BP Neural Network

机译:基于BP神经网络的仿人机器人手臂无传感器外力检测方法。

获取原文

摘要

In order to improve the safety performance of the robot, this paper proposes an external force detection method for humanoid robot arm without using joint torque sensors, which can detect the external force of the joint space in real time during the operation of the robot. First, Analyses on the structure of the humanoid robot arm is performed, and the model of robot external force detection is established based on robot dynamics and motor dynamics. Then, the error of detection model is analyzed, and the robot dynamic model error is compensated by using the BP network, in order to obtain more accurate external force detection value of the robot. Experiments show that the method can effectively improve the detection accuracy, and the obtained external force detection data can be applied not only to the collision detection in the static state of the robot, but also to the online collision detection when the robot is running, which can ensure the safe operation of the robot.
机译:为了提高机器人的安全性能,本文提出了一种无需使用关节扭矩传感器的人形机器人手臂外力检测方法,该方法可以在机器人运行过程中实时检测关节空间的外力。首先,对人形机器人手臂进行结构分析,并基于机器人动力学和电机动力学建立了机器人外力检测模型。然后,分析检测模型的误差,并利用BP网络对机器人的动力学模型误差进行补偿,以获得更准确的机器人外力检测值。实验表明,该方法可以有效地提高检测精度,所获得的外力检测数据不仅可以应用于机器人静止状态下的碰撞检测,还可以应用于机器人运行时的在线碰撞检测。可以确保机器人的安全运行。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号