Evaluation of Terrain Parameter Estimation using a Stochastic Terrain Model

被引:1
|
作者
Dumond, Danielle A. [1 ]
Ray, Laura E. [1 ]
Trautmann, Eric [1 ]
机构
[1] Dartmouth Coll, Thayer Sch Engn, Hanover, NH 03755 USA
来源
关键词
Mobile robot dynamics; terrain factors;
D O I
10.1117/12.817737
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Autonomous vehicles driving on off-road terrain exhibit substantial variation in mobility characteristics even when the terrain is horizontal and qualitatively homogeneous. This paper presents a simple stochastic model for characterizing observed variability in vehicle response to terrain and for representing transitions between homogeneous terrain with local variability or between heterogeneous terrain types. Such a model provides a means for more realistic evaluation of terrain parameter estimation methods through simulation. A stochastic terrain model in which friction angle and soil cohesion are represented by Gaussian random variables qualitatively represents observed variability in traction vs. slip characteristics measured experimentally. The stochastic terrain model is used to evaluate a terrain parameter estimation method in which terrain forces are first estimated independent of a terrain model, and subsequently, parameters of a terrain model, such as soil cohesion, friction angle, and stress distribution parameters are determined from estimated vehicle-terrain forces. Simulation results show drawbar pull vs. slip characteristics resulting from terrain parameter estimation are within statistical bounds established by the stochastic terrain model.
引用
收藏
页数:10
相关论文
共 50 条
  • [41] Recent developments in terrain identification, classification, parameter estimation for the navigation of autonomous robots
    M. G. Harinarayanan Nampoothiri
    B Vinayakumar
    Youhan Sunny
    Rahul Antony
    SN Applied Sciences, 2021, 3
  • [42] Slip parameter estimation for tele-operated ground vehicles in slippery terrain
    Song, X.
    Seneviratne, L. D.
    Althoefer, K.
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING, 2011, 225 (I6) : 814 - 830
  • [43] The Simultaneous Estimation Method of Terrain Parameter and Vehicle Dynamics Variables for Agricultural Vehicle
    Suzuki, Makoto
    Fujimoto, Hiroshi
    Hori, Yoichi
    2019 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS (ICM), 2019, : 596 - 601
  • [44] Evaluation of fractal terrain model for vehicle dynamic simulations
    Dawkins, Jeremy J.
    Bevly, David M.
    Jackson, Robert L.
    JOURNAL OF TERRAMECHANICS, 2012, 49 (06) : 299 - 307
  • [45] Target detection in infrared and SAR terrain images using a non-Gaussian stochastic model
    Chapple, PB
    Bertilone, DC
    Caprari, RS
    Angeli, S
    Newsam, GN
    TARGETS AND BACKGROUNDS: CHARACTERIZATION AND REPRESENTATION V, 1999, 3699 : 122 - 132
  • [46] Terrain slope parameter recognition for exoskeleton robot in urban multi-terrain environments
    Guo, Ran
    Li, Wenjiang
    He, Yulong
    Zeng, Tangjian
    Li, Bin
    Song, Guangkui
    Qiu, Jing
    COMPLEX & INTELLIGENT SYSTEMS, 2024, 10 (02) : 3107 - 3118
  • [47] RANDOM TERRAIN MODEL
    李清
    高伟
    陆宇平
    沈春林
    Transactions of Nanjing University of Aeronautics & Astronau, 1997, (01) : 19 - 24
  • [48] Model Based Off-Road Terrain Profile Estimation
    Dawkins, Jeremy J.
    2014 AMERICAN CONTROL CONFERENCE (ACC), 2014, : 2792 - 2797
  • [49] Terrain slope parameter recognition for exoskeleton robot in urban multi-terrain environments
    Ran Guo
    Wenjiang Li
    Yulong He
    Tangjian Zeng
    Bin Li
    Guangkui Song
    Jing Qiu
    Complex & Intelligent Systems, 2024, 10 : 3107 - 3118
  • [50] Power Demand Forecasting Using Stochastic Model: Parameter Estimation
    Ma, Ruihong
    Wu, Rentao
    Khanwala, Mustafa A.
    Li, Dan
    Dang, Shuping
    2015 MODERN ELECTRIC POWER SYSTEMS (MEPS), 2015,