Camera-Based Articulation Angle Sensing for Heavy Goods Vehicles

被引:1
|
作者
de Saxe, Christopher [1 ,2 ]
Cebon, David [1 ]
机构
[1] Univ Cambridge, Dept Engn, Trumpington St, Cambridge CB2 1PZ, England
[2] Univ Witwatersrand, Sch Mech Ind & Aeronaut Engn, ZA-2000 Johannesburg, South Africa
基金
英国工程与自然科学研究理事会;
关键词
Cameras; Agricultural machinery; Sensors; Simultaneous localization and mapping; Shape; Task analysis; Kalman filters; Articulated vehicles; articulation angle; computer vision; sensors; SLAM;
D O I
10.1109/TVT.2021.3091759
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Articulation angle sensing is an essential component of manoeuvrability and stability control systems for articulated heavy goods vehicles, particularly long combination vehicles. Existing solutions to this sensing task are limited by reliance on trailer modifications or information or by measurement accuracy, or both, restricting commercial adoption. In this paper we present a purely tractor-based sensor concept comprising a rear-facing camera and the parallel tracking and mapping (PTAM) image processing algorithm. The system requires no prior knowledge of or modifications to the trailer, is compatible with planar and non-planar trailer shapes, and with multiply-articulated vehicle combinations. The system is validated in full-scale vehicle tests on both a tractor semi-trailer combination and a truck and full-trailer combination, demonstrating robust performance in a number of conditions, including trailers with non-planar geometry and with minimal visual features. Average RMS measurement errors of 1.19, 1.03 and 1.53 degrees were demonstrated for the semi-trailer and full-trailer (drawbar and semi-trailer) respectively. This compares favourably with the state-of-the-art in the published literature. A number of improvements are proposed for future development based on the observations in this research.
引用
收藏
页码:7522 / 7535
页数:14
相关论文
共 50 条
  • [21] Camera-based weight estimation
    Laufer, Patrick
    VDI Berichte, 2022, 2022 (2407): : 291 - 298
  • [22] Camera-based colour inspection
    Nobbs, J.H.
    Connolly, C.
    Sensor Review, 2000, 20 (01) : 14 - 19
  • [23] Intersection Safety for Heavy Goods Vehicles
    Ahrholdt, M.
    Grubb, Gr.
    Agardt, E.
    ADVANCED MICROSYSTEMS FOR AUTOMOTIVE APPLICATIONS 2009, 2009, : 87 - 96
  • [24] Integrated camera-based navigation
    Hafskjold, BH
    Jalving, B
    Hagen, PE
    Gade, K
    JOURNAL OF NAVIGATION, 2000, 53 (02): : 237 - 245
  • [25] Drivability Analysis of Heavy Goods Vehicles
    Abuasaker, Sufyan
    Sorniotti, Aldo
    SAE INTERNATIONAL JOURNAL OF COMMERCIAL VEHICLES, 2010, 3 (01) : 195 - 215
  • [26] IMPACT SPEED OF HEAVY GOODS VEHICLES
    DAVIES, PA
    LEES, FP
    JOURNAL OF HAZARDOUS MATERIALS, 1991, 26 (02) : 213 - 217
  • [27] Noninvasive Concept for Optical Ethanol Sensing on the Skin Surface with Camera-Based Quantification
    Hair, Mindy E.
    Gerkman, Ryan
    Mathis, Adrianna I.
    Halamkova, Lenka
    Halamek, Jan
    ANALYTICAL CHEMISTRY, 2019, 91 (24) : 15860 - 15865
  • [28] Camera-based optical palpation
    Sanderson, Rowan W.
    Fang, Qi
    Curatolo, Andrea
    Adams, Wayne
    Lakhiani, Devina D.
    Ismail, Hina M.
    Foo, Ken Y.
    Dessauvagie, Benjamin F.
    Latham, Bruce
    Yeomans, Chris
    Saunders, Christobel M.
    Kennedy, Brendan F.
    SCIENTIFIC REPORTS, 2020, 10 (01)
  • [29] CCD camera-based range sensing with FPGA for real-time processing
    Lin, CS
    Kim, H
    EMBEDDED SOFTWARE AND SYSTEMS, PROCEEDINGS, 2005, 3820 : 398 - 407
  • [30] Preserving anonymity in indoor location system by context sensing and camera-based tracking
    Iwamoto, Takeshi
    Kobayashi, Arei
    Nishiyama, Satoshi
    LOCATION- AND CONTEXT-AWARENESS, 2007, 4718 : 263 - +