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Title: High-precision control of tracked field robots in the presence of unknown traction coefficients

Abstract

Accurate steering through crop rows that avoids crop damage is one of the most important tasks for agricultural robots utilized in various field operations, such as monitoring, mechanical weeding, or spraying. In practice, varying soil conditions can result in off-track navigation due to unknown traction coefficients so that it can cause crop damage. To address this problem, this work presents the development, application, and experimental results of a real-time receding horizon estimation and control (RHEC) framework applied to a fully autonomous mobile robotic platform to increase its steering accuracy. Recent advances in cheap and fast microprocessors, as well as advances in solution methods for nonlinear optimization problems, have made nonlinear receding horizon control (RHC) and receding horizon estimation (RHE) methods suitable for field robots that require high-frequency (milliseconds) updates. A real-time RHEC framework is developed and applied to a fully autonomous mobile robotic platform designed by the authors for in-field phenotyping applications in sorghum fields. Nonlinear RHE is used to estimate constrained states and parameters, and nonlinear RHC is designed based on an adaptive system model that contains time-varying parameters. The capabilities of the real-time RHEC framework are verified experimentally, and the results show an accurate tracking performance on amore » bumpy and wet soil field. Finally, the mean values of the Euclidean error and required computation time of the RHEC framework are equal to 0.0423 m and 0.88 ms, respectively.« less

Authors:
ORCiD logo [1];  [2];  [3];  [2]
  1. University of Illinois at Urbana-Champaign, Urbana, IL (United States); Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
  2. University of Illinois at Urbana-Champaign, Urbana, IL (United States)
  3. Iowa State Univ., Ames, IA (United States)
Publication Date:
Research Org.:
University of Illinois at Urbana-Champaign, Urbana, IL (United States)
Sponsoring Org.:
USDOE Advanced Research Projects Agency - Energy (ARPA-E)
OSTI Identifier:
1466744
Alternate Identifier(s):
OSTI ID: 1457828
Grant/Contract Number:  
AR0000598
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Field Robotics
Additional Journal Information:
Journal Volume: 35; Journal Issue: 7; Journal ID: ISSN 1556-4959
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; 54 ENVIRONMENTAL SCIENCES; agriculture; control; field robot; mobile robot; path tracking; robot control

Citation Formats

Kayacan, Erkan, Young, Sierra N., Peschel, Joshua M., and Chowdhary, Girish. High-precision control of tracked field robots in the presence of unknown traction coefficients. United States: N. p., 2018. Web. doi:10.1002/rob.21794.
Kayacan, Erkan, Young, Sierra N., Peschel, Joshua M., & Chowdhary, Girish. High-precision control of tracked field robots in the presence of unknown traction coefficients. United States. doi:https://doi.org/10.1002/rob.21794
Kayacan, Erkan, Young, Sierra N., Peschel, Joshua M., and Chowdhary, Girish. Fri . "High-precision control of tracked field robots in the presence of unknown traction coefficients". United States. doi:https://doi.org/10.1002/rob.21794. https://www.osti.gov/servlets/purl/1466744.
@article{osti_1466744,
title = {High-precision control of tracked field robots in the presence of unknown traction coefficients},
author = {Kayacan, Erkan and Young, Sierra N. and Peschel, Joshua M. and Chowdhary, Girish},
abstractNote = {Accurate steering through crop rows that avoids crop damage is one of the most important tasks for agricultural robots utilized in various field operations, such as monitoring, mechanical weeding, or spraying. In practice, varying soil conditions can result in off-track navigation due to unknown traction coefficients so that it can cause crop damage. To address this problem, this work presents the development, application, and experimental results of a real-time receding horizon estimation and control (RHEC) framework applied to a fully autonomous mobile robotic platform to increase its steering accuracy. Recent advances in cheap and fast microprocessors, as well as advances in solution methods for nonlinear optimization problems, have made nonlinear receding horizon control (RHC) and receding horizon estimation (RHE) methods suitable for field robots that require high-frequency (milliseconds) updates. A real-time RHEC framework is developed and applied to a fully autonomous mobile robotic platform designed by the authors for in-field phenotyping applications in sorghum fields. Nonlinear RHE is used to estimate constrained states and parameters, and nonlinear RHC is designed based on an adaptive system model that contains time-varying parameters. The capabilities of the real-time RHEC framework are verified experimentally, and the results show an accurate tracking performance on a bumpy and wet soil field. Finally, the mean values of the Euclidean error and required computation time of the RHEC framework are equal to 0.0423 m and 0.88 ms, respectively.},
doi = {10.1002/rob.21794},
journal = {Journal of Field Robotics},
number = 7,
volume = 35,
place = {United States},
year = {2018},
month = {6}
}

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    Works referencing / citing this record:

    Modeling and control of a spherical rolling robot: a decoupled dynamics approach
    journal, August 2011


    Online Terrain Parameter Estimation for Wheeled Mobile Robots With Application to Planetary Rovers
    journal, October 2004


    Robust Trajectory Tracking Error Model-Based Predictive Control for Unmanned Ground Vehicles
    journal, April 2016

    • Kayacan, Erkan; Ramon, Herman; Saeys, Wouter
    • IEEE/ASME Transactions on Mechatronics, Vol. 21, Issue 2
    • DOI: 10.1109/tmech.2015.2492984

    Real-time optimization and nonlinear model predictive control of processes governed by differential-algebraic equations
    journal, June 2002


    Road-map–assisted standoff tracking of moving ground vehicle using nonlinear model predictive control
    journal, April 2015

    • Hyondong Oh, ; Tsourdos, Antonios
    • IEEE Transactions on Aerospace and Electronic Systems, Vol. 51, Issue 2
    • DOI: 10.1109/taes.2014.130688

    ACADO toolkit-An open-source framework for automatic control and dynamic optimization
    journal, May 2010

    • Houska, Boris; Ferreau, Hans Joachim; Diehl, Moritz
    • Optimal Control Applications and Methods, Vol. 32, Issue 3
    • DOI: 10.1002/oca.939

    Non-linear model predictive control for constrained robot navigation in row crops
    conference, March 2015

    • Utstumo, Trygve; Berge, Therese W.; Gravdahl, Jan Tommy
    • 2015 IEEE International Conference on Industrial Technology (ICIT)
    • DOI: 10.1109/icit.2015.7125124

    Receding horizon tracking control of wheeled mobile robots
    journal, July 2006


    Genetic and biotechnological approaches for biofuel crop improvement
    journal, April 2010


    Velocity Control of a Spherical Rolling Robot Using a Grey-PID Type Fuzzy Controller With an Adaptive Step Size
    journal, January 2012


    Critical Evaluation of Extended Kalman Filtering and Moving-Horizon Estimation
    journal, April 2005

    • Haseltine, Eric L.; Rawlings, James B.
    • Industrial & Engineering Chemistry Research, Vol. 44, Issue 8
    • DOI: 10.1021/ie034308l

    Constrained model predictive control: Stability and optimality
    journal, June 2000


    Tracking-error model-based predictive control for mobile robots in real time
    journal, June 2007


    Predictive Active Steering Control for Autonomous Vehicle Systems
    journal, May 2007

    • Falcone, Paolo; Borrelli, Francesco; Asgari, Jahan
    • IEEE Transactions on Control Systems Technology, Vol. 15, Issue 3
    • DOI: 10.1109/tcst.2007.894653

    Genome studies and molecular genetics—from sequence to crops: genomics comes of age
    journal, April 2009


    A Reactive Walking Pattern Generator Based on Nonlinear Model Predictive Control
    journal, January 2017

    • Naveau, M.; Kudruss, M.; Stasse, O.
    • IEEE Robotics and Automation Letters, Vol. 2, Issue 1
    • DOI: 10.1109/lra.2016.2518739

    Nonlinear modeling and identification of an autonomous tractor–trailer system
    journal, August 2014


    Robust Tube-Based Decentralized Nonlinear Model Predictive Control of an Autonomous Tractor-Trailer System
    journal, February 2015

    • Kayacan, Erkan; Kayacan, Erdal; Ramon, Herman
    • IEEE/ASME Transactions on Mechatronics, Vol. 20, Issue 1
    • DOI: 10.1109/tmech.2014.2334612

    Multiobjective $H_{\infty }$ Control for String Stability of Cooperative Adaptive Cruise Control Systems
    journal, March 2017


    Oil supply limits and the continuing financial crisis
    journal, January 2012


    Robust sampling-based motion planning for autonomous tracked vehicles in deformable high slip terrain
    conference, May 2016

    • Lee, Sang Uk; Gonzalez, Ramon; Iagnemma, Karl
    • 2016 IEEE International Conference on Robotics and Automation (ICRA)
    • DOI: 10.1109/icra.2016.7487413

    Distributed nonlinear model predictive control of an autonomous tractor–trailer system
    journal, December 2014


    Future Scenarios for Plant Phenotyping
    journal, April 2013


    Genetic modification of plant cell walls to enhance biomass yield and biofuel production in bioenergy crops
    journal, September 2016


    Adaptive tracking control of a nonholonomic mobile robot
    journal, January 2000

    • Fukao, T.; Nakagawa, H.; Adachi, N.
    • IEEE Transactions on Robotics and Automation, Vol. 16, Issue 5
    • DOI: 10.1109/70.880812

    Modeling and identification of the yaw dynamics of an autonomous tractor
    conference, June 2013


    Robust motion planning methodology for autonomous tracked vehicles in rough environment using online slip estimation
    conference, October 2016

    • Lee, Sang Uk; Iagnemma, Karl
    • 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
    • DOI: 10.1109/iros.2016.7759528

    Robust Model Predictive Control of Systems by Modeling Mismatched Uncertainty
    journal, January 2016


    Navigation system for agricultural machines: Nonlinear Model Predictive path tracking
    journal, March 2012


    High-speed moving horizon estimation based on automatic code generation
    conference, December 2012

    • Ferreau, Hans Joachim; Kraus, Tom; Vukov, Milan
    • 2012 IEEE 51st Annual Conference on Decision and Control (CDC), 2012 IEEE 51st IEEE Conference on Decision and Control (CDC)
    • DOI: 10.1109/cdc.2012.6426428

    Estimation of Terrain Forces and Parameters for Rigid-Wheeled Vehicles
    journal, June 2009


    Real-time nonlinear MPC and MHE for a large-scale mechatronic application
    journal, December 2015


    Towards agrobots: Identification of the yaw dynamics and trajectory tracking of an autonomous tractor
    journal, July 2015


    Tracking control of unicycle-modeled mobile robots using a saturation feedback controller
    journal, March 2001

    • Ti-Chung Lee,
    • IEEE Transactions on Control Systems Technology, Vol. 9, Issue 2
    • DOI: 10.1109/87.911382

    Design and Implementation of Model-Predictive Control With Friction Compensation on an Omnidirectional Mobile Robot
    journal, April 2014

    • Barreto S., Julio Cesar Lins; Conceicao, Andre Gustavo Scolari; Dorea, Carlos E. T.
    • IEEE/ASME Transactions on Mechatronics, Vol. 19, Issue 2
    • DOI: 10.1109/tmech.2013.2243161

    Centralized, decentralized and distributed nonlinear model predictive control of a tractor-trailer system: A comparative study
    conference, July 2016

    • Kayacan, Erkan; Peschel, Joshua M.; Kayacan, Erdal
    • 2016 American Control Conference (ACC)
    • DOI: 10.1109/acc.2016.7525615

    An online active set strategy to overcome the limitations of explicit MPC
    journal, January 2008

    • Ferreau, H. J.; Bock, H. G.; Diehl, M.
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    A moving horizon-based approach for least-squares estimation
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    • Robertson, Douglas G.; Lee, Jay H.; Rawlings, James B.
    • AIChE Journal, Vol. 42, Issue 8
    • DOI: 10.1002/aic.690420811

    Towards Agrobots: Trajectory Control of an Autonomous Tractor Using Type-2 Fuzzy Logic Controllers
    journal, February 2015

    • Kayacan, Erdal; Kayacan, Erkan; Ramon, Herman
    • IEEE/ASME Transactions on Mechatronics, Vol. 20, Issue 1
    • DOI: 10.1109/tmech.2013.2291874

    Sliding mode control for systems with mismatched time-varying uncertainties via a self-learning disturbance observer
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    • DOI: 10.3390/su11236751