Modeling and Control of General Hydraulic Excavator for Human-in-the-loop Automation

被引:2
作者
Chen, Guangda [1 ,4 ]
Gan, Yinghao [1 ]
Chen, Jiayi [2 ]
Shi, Shuanwu [3 ]
Chen, Wei [1 ]
Chen, Yingfeng [1 ]
Xiong, Rong [4 ]
Fan, Changjie [1 ]
机构
[1] Fuxi Robot NetEase, Hangzhou, Peoples R China
[2] Hangzhou Dianzi Univ, Coll Comp Sci & Technol, Hangzhou, Peoples R China
[3] Zhejiang Univ Technol, Dept Automat, Hangzhou, Peoples R China
[4] Zhejiang Univ, State Key Lab Ind Control & Technol, Hangzhou, Peoples R China
来源
2023 IEEE 35TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, ICTAI | 2023年
关键词
D O I
10.1109/ICTAI59109.2023.00110
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
As labor shortages and safety regulations become more prominent, the need for human-in-the-loop automation of excavators is increasing. To meet this demand, we have developed a comprehensive modeling method for the excavator arm using nonlinear optimization approaches, including a simplified model that maps the task space to the joint space, as well as an equivalent model that maps the joint space to the actuator space. These models were then used to build a feedforward-PID joint velocity controller and a joint trajectory controller combined with position feedback, which forms the core of our proposed semi-automatic control system for the excavator arm. Our deployment scheme is simple and efficient, and has been deployed on two excavators of different makes and sizes. Experiments show that our deployment scheme performs well on both excavators, with an average error of 0.05 rad/s for the velocity controller and less than 5 cm for the trajectory controller. Using our semi-automatic system, we have completed demonstration experiments for precise digging and grading operations. A demonstration video can be found at https://youtu.be/N6I0WZGSF68.
引用
收藏
页码:708 / 716
页数:9
相关论文
共 22 条
  • [1] The development, control and operation of an autonomous robotic excavator
    Bradley, DA
    Seward, DW
    [J]. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 1998, 21 (01) : 73 - 97
  • [2] Cannon H. N., 1999, Extended earthmoving with an autonomous excavator
  • [3] Coleman D, 2014, Arxiv, DOI arXiv:1404.3785
  • [4] Key challenges in automation of earth-moving machines
    Dadhich, S.
    Bodin, U.
    Andersson, U.
    [J]. AUTOMATION IN CONSTRUCTION, 2016, 68 : 212 - 222
  • [5] A General Approach for the Automation of Hydraulic Excavator Arms Using Reinforcement Learning
    Egli, Pascal
    Hutter, Marco
    [J]. IEEE ROBOTICS AND AUTOMATION LETTERS, 2022, 7 (02): : 5679 - 5686
  • [6] Halbach E, 2019, IEEE INT CONF ROBOT, P980, DOI [10.1109/icra.2019.8793468, 10.1109/ICRA.2019.8793468]
  • [7] HEAP- The autonomous walking excavator
    Jud, Dominic
    Kerscher, Simon
    Wermelinger, Martin
    Jelavic, Edo
    Egli, Pascal
    Leemann, Philipp
    Hottiger, Gabriel
    Hutter, Marco
    [J]. AUTOMATION IN CONSTRUCTION, 2021, 129
  • [8] Task planning strategy and path similarity analysis for an autonomous excavator
    Kim, Jeonghwan
    Lee, Dong-eun
    Seo, Jongwon
    [J]. AUTOMATION IN CONSTRUCTION, 2020, 112
  • [9] Challenges, tasks, and opportunities in teleoperation of excavator toward human-in-the-loop construction automation
    Lee, Jin Sol
    Ham, Youngjib
    Park, Hangue
    Kim, Jeonghee
    [J]. AUTOMATION IN CONSTRUCTION, 2022, 135
  • [10] Lee JS, 2022, CONSTRUCTION RESEARCH CONGRESS 2022: COMPUTER APPLICATIONS, AUTOMATION, AND DATA ANALYTICS, P757