Optimization-based robot compliance control: Geometric and linear quadratic approaches

被引:31
|
作者
Matinfar, M [1 ]
Hashtrudi-Zaad, K [1 ]
机构
[1] Queens Univ, Dept Elect & Comp Engn, Kingston, ON, Canada
来源
关键词
robot compliance control; robot impedance control; quadratic optimal control;
D O I
10.1177/0278364905056347
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Impedance control is a compliance control strategy capable of accommodating both unconstrained and constrained motions. The performance of impedance controllers depends heavily upon environment dynamics and the choice of target impedance. To maintain performance for a wide range of environments, target impedance needs to be adjusted adaptively. In this paper a geometric view on impedance control is developed for stiff environments, resulting in a "static-optimized" controller that minimizes a combined generalized position and force trajectory error metric. To incorporate the dynamic nature of the manipulator-environment system, a new cost function is considered. A classic quadratic optimal control strategy is employed to design a novel adaptive compliance controller with control parameters adjusted based upon environment stiffness and damping. In steady state, the proposed controller ultimately implements the static-optimized impedance controller. Simulation and experimental results indicate that the proposed optimal controller offers smoother transient response and a better trade-off between position and force regulation.
引用
收藏
页码:645 / 656
页数:12
相关论文
共 50 条
  • [21] Optimization-Based Whole-Body Control of a Series Elastic Humanoid Robot
    Hopkins, Michael A.
    Leonessa, Alexander
    Lattimer, Brian Y.
    Hong, Dennis W.
    INTERNATIONAL JOURNAL OF HUMANOID ROBOTICS, 2016, 13 (01)
  • [22] An optimization-based shared control framework with applications in multi-robot systems
    Hao FANG
    Chengsi SHANG
    Jie CHEN
    Science China(Information Sciences), 2018, 61 (01) : 261 - 263
  • [23] Augmented Hierarchical Quadratic Programming for Adaptive Compliance Robot Control
    Tassi, Francesco
    De Momi, Elena
    Ajoudani, Arash
    2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021), 2021, : 3568 - 3574
  • [24] Optimization-Based Approaches for Bioethanol Supply Chains
    Akgul, Ozlem
    Zamboni, Andrea
    Bezzo, Fabrizio
    Shah, Nilay
    Papageorgiou, Lazaros G.
    INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2011, 50 (09) : 4927 - 4938
  • [25] Approaches to motion planning for a spherical robot based on differential geometric control theory
    Li, Tuanjie
    Zhang, Yigang
    Zhang, Yan
    WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, 2006, : 66 - 66
  • [26] Magnetic suspension control system based on stochastic linear quadratic optimization
    2005, East China University of Science and Technology, Shanghai, China (31):
  • [27] H∞ optimization-based decentralized control of linear interconnected systems with nonlinear interconnections
    Tlili, Ali Sghaier
    Braiek, Naceur Benhadj
    JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2014, 351 (06): : 3286 - 3304
  • [28] Research into the Beetle Antennae Optimization-Based PID Servo System Control of an Industrial Robot
    Ji, Tian
    Wei, Haoran
    Wang, Jun
    Tian, Shaoqing
    Yao, Yi
    Hu, Shukai
    MATHEMATICS, 2023, 11 (19)
  • [29] Grey Wolf Optimization-Based Second Order Sliding Mode Control for Inchworm Robot
    Roy, Rupam Gupta
    Ghoshal, Dibyendu
    ROBOTICA, 2020, 38 (09) : 1539 - 1557
  • [30] Particle Swarm Optimization-based Receding Horizon Control for Multi-Robot Formation
    Lee, Seung-Mok
    Myung, Hyun
    2012 9TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS AND AMBIENT INTELLIGENCE (URAL), 2012, : 625 - 626