...
首页> 外文期刊>International journal of intelligent robotics and applications >Robust state dependent Riccati equation variable impedance control for robotic force-tracking tasks
【24h】

Robust state dependent Riccati equation variable impedance control for robotic force-tracking tasks

机译:健壮的状态依赖的黎卡提微分方程变量阻抗控制机器人force-tracking任务

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Industrial robots are increasingly used in highly flexible interaction tasks, where the intrinsic variability makes difficult to pre-program the manipulator for all the different scenarios. In such applications, interaction environments are commonly (partially) unknown to the robot, requiring the implemented controllers to take in charge for the stability of the interaction. While standard controllers are sensor-based, there is a growing need to make sensorless robots (i.e., most of the commercial robots are not equipped with force/torque sensors) able to sense the environment, properly reacting to the established interaction. This paper proposes a new methodology to sensorless force control manipulators. On the basis of sensorless Cartesian impedance control, an Extended Kalman Filter (EKF) is designed to estimate the interaction exchanged between the robot and the environment. Such an estimation is then used in order to close a robust high-performance force loop, designed exploiting a variable impedance control and a State Dependent Riccati Equation (SDRE) force controller. The described approach has been validated in simulations. A Franka EMIKA panda robot has been considered as a test platform. A probing task involving different materials (i.e., with different stiffness properties) has been considered to show the capabilities of the developed EKF (able to converge with limited errors) and controller (preserving stability and avoiding overshoots). The proposed controller has been compared with an LQR controller to show its improved performance.
机译:越来越多的工业机器人用于高度灵活的交互任务,内在的地方变化使得很难pre-program机械手的所有不同的场景。这样的应用程序中,交互环境通常(部分)未知的机器人,要求控制器来实现收费的稳定交互。虽然标准控制器是基于传感器,人们越来越需要无传感器的机器人(例如,大部分的商业机器人配备了力/力矩传感器)能够有意义环境,妥善应对建立交互。无传感器力控制的新方法操纵者。笛卡尔阻抗控制,扩展卡尔曼滤波过滤器(EKF)旨在估计交互和机器人之间的交换环境。关闭一个健壮的高性能的力量循环,设计利用可变阻抗控制和状态依赖的黎卡提微分方程(SDRE)力控制器。在模拟验证。熊猫机器人已被视为测试平台。材料(例如,有不同的刚度属性)一直认为显示功能发达卡尔曼滤波器(能够收敛与有限的错误)和控制器(保持稳定,避免过激的)。提出的控制器相比,一个等控制器显示其改进的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
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