Real-Time Motion Planning of a Hydraulic Excavator using Trajectory Optimization and Model Predictive Control

被引:15
|
作者
Lee, Dongjae [1 ,2 ]
Jang, Inkyu [1 ,2 ]
Byun, Jeonghyun [1 ,2 ]
Seo, Hoseong [1 ,2 ]
Kim, H. Jin [1 ,2 ]
机构
[1] Seoul Natl Univ SNU, Dept Aerosp Engn, Seoul 08826, South Korea
[2] Automat & Syst Res Inst ASRI, Seoul 08826, South Korea
关键词
D O I
10.1109/IROS51168.2021.9635965
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Automation of excavation tasks requires real-time trajectory planning satisfying various constraints. To guarantee both constraint feasibility and real-time trajectory replannability, we present an integrated framework for realtime optimization-based trajectory planning of a hydraulic excavator. The proposed framework is composed of two main modules: a global planner and a real-time local planner. The global planner computes the entire global trajectory considering excavation volume and energy minimization while the local counterpart tracks the global trajectory in a receding horizon manner, satisfying dynamic feasibility, physical constraints, and disturbance-awareness. We validate the proposed planning algorithm in a simulation environment where two types of operations are conducted in the presence of emulated disturbance from hydraulic friction and soil-bucket interaction: shallow and deep excavation. The optimized global trajectories are obtained in an order of a second, which is tracked by the local planner at faster than 30 Hz. To the best of our knowledge, this work presents the first real-time motion planning framework that satisfies constraints of a hydraulic excavator, such as force/torque, power, cylinder displacement, and flow rate limits.
引用
收藏
页码:2135 / 2142
页数:8
相关论文
共 50 条
  • [1] Real-Time Trajectory Generation using Model Predictive Control
    Ardakani, M. Mahdi Ghazaei
    Olofsson, Bjorn
    Robertsson, Anders
    Johansson, Rolf
    [J]. 2015 INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING (CASE), 2015, : 942 - 948
  • [2] Real-time Cooperative Motion Planning using Efficient Model Predictive Contouring Control
    Pauls, Jan-Hendrik
    Boxheimer, Mario
    Stiller, Christoph
    [J]. 2022 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2022, : 1495 - 1503
  • [3] Trajectory Generation for a Hydraulic Mini Excavator using Nonlinear Model Predictive Control
    Wind, Hannes
    Renner, Anton
    Bender, Frank A.
    Sawodny, Oliver
    [J]. 2020 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY (ICIT), 2020, : 107 - 112
  • [4] Real-Time Motion Planning of Legged Robots: A Model Predictive Control Approach
    Farshidian, Farbod
    Jelavic, Edo
    Satapathy, Asutosh
    Giftthaler, Markus
    Buchli, Jonas
    [J]. 2017 IEEE-RAS 17TH INTERNATIONAL CONFERENCE ON HUMANOID ROBOTICS (HUMANOIDS), 2017, : 577 - 584
  • [5] Model Predictive Trajectory Tracking Control for Hydraulic Excavator on Digging Operation
    Tomatsu, Takumi
    Nonaka, Kenichiro
    Sekiguchui, Kazuma
    Suzuki, Katsumasa
    [J]. 2015 IEEE CONFERENCE ON CONTROL AND APPLICATIONS (CCA 2015), 2015, : 1136 - 1141
  • [6] Integration of real-time optimization and model predictive control
    Adetola, V.
    Guay, M.
    [J]. JOURNAL OF PROCESS CONTROL, 2010, 20 (01) : 125 - 133
  • [7] Local Real-Time Motion Planning Using Evolutionary Optimization
    Mueller, Steffen
    Trinh, Thanh Q.
    Gross, Horst-Michael
    [J]. TOWARDS AUTONOMOUS ROBOTIC SYSTEMS (TAROS 2017), 2017, 10454 : 211 - 221
  • [8] Distributed Model Predictive Contouring Control for Real-Time Multi-Robot Motion Planning
    Xin, Jianbin
    Qu, Yaoguang
    Zhang, Fangfang
    Negenborn, Rudy
    [J]. Complex System Modeling and Simulation, 2022, 2 (04): : 273 - 287
  • [9] Real-Time Trajectory Optimization under Motion Uncertainty using a GPU
    Heinrich, Steffen
    Zoufahl, Andre
    Rojas, Raul
    [J]. 2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2015, : 3572 - 3577
  • [10] Real-time economic optimization for a fermentation process using Model Predictive Control
    Petersen, Lars Norbert
    Jorgensen, John Bagterp
    [J]. 2014 EUROPEAN CONTROL CONFERENCE (ECC), 2014, : 1831 - 1836