Design and experiment of visual navigated UGV for orchard based on Hough matrix and RANSAC
Abstract
Keywords: visual navigation, unmanned ground vehicle, Hough matrix, RANSAC algorithm, orchard, H-component
DOI: 10.25165/j.ijabe.20211406.5953
Citation: Zhou M K, Xia J F, Yang F, Zheng K, Hu M J, Li D, et al. Design and experiment of visual navigated UGV for orchard based on Hough matrix and RANSAC. Int J Agric & Biol Eng, 2021; 14(6): 176–184.
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Lemos RAD, Nogueira LACDO, Ribeiro AM, Mirisola L G B, Koyama M F, de Paiva E C, et al. Unisensory intra-row navigation strategy for orchards environments based on sensor laser. Congresso Brasileiro de Automática, 2018; 22: 0400. doi: 10.20906/CPS/CBA2018-0400.
Thanpattranon P, Ahamed T, Takigawa T. Navigation of autonomous tractor for orchards and plantations using a laser range finder: Automatic control of trailer position with tractor. Biosystems Engineering, 2016; 147: 90–103.
Blok P M, van Boheemen K, van Evert F K, IJsselmuiden J, Kim G-H. Robot navigation in orchards with localization based on Particle filter and Kalman filter. Computers and Electronics in Agriculture, 2019; 157: 261–269.
Passalaqua B P, Molin J P. Path errors in sugarcane transshipment trailers. Engenharia Agrícola, 2020; 40(2): 223–231.
Luo C, Mohsenimanesh A, Laguë C. Parallel point-to-point tracking for agricultural Wide-Span Implement Carrier (WSIC). Computers and Electronics in Agriculture, 2018, 153: 302–312.
Sumesh K C, Ninsawat S, Som-ard J. Integration of RGB-based vegetation index, crop surface model and object-based image analysis approach for sugarcane yield estimation using unmanned aerial vehicle. Computers and Electronics in Agriculture, 2021, 180: 105903. doi: 10.1016/j.compag.2020.105903.
Meng Q K, He J, Qiu R C, Ma X D, Si Y S, Zhang M, et al. Crop recognition and navigation line detection in natural environment based on machine vision. Acta Optica Sinica, 2014; 34(7): 180–186. (in Chinese)
Oksanen T. Laser scanner based collision prevention system for autonomous agricultural tractor. Agronomy Research, 2015; 13(1): 167–172.
Zhang H C, Zheng J Q, Dorr G, Zhou H P, Ge Y F. Testing of GPS accuracy for precision forestry applications. Arabian Journal for Science and Engineering, 2014; 39(1): 237–245.
Bengochea-Guevara J M, Conesa-Muñoz J, Andújar D, Ribeiro A. Merge fuzzy visual servoing and GPS-based planning to obtain a proper navigation behavior for a small crop-inspection robot. Sensors, 2016; 16(3): 276. doi: 10.3390/s16030276.
Choi K H, Han S K, Han S H, Park K H, Kim K S, Kim S. Morphology-based guidance line extraction for an autonomous weeding robot in paddy fields. Computers and Electronics in Agriculture, 2015; 113: 266–274.
Yao L J, Hu D, Yang Z D, Li H B, Qian M B. Depth recovery for unstructured farmland road image using an improved SIFT algorithm. Int J Agric & Biol Eng, 2019; 12(4): 141–147.
Chang Q X, Xiong Z K. Vision-aware target recognition toward autonomous robot by Kinect sensors. Signal Processing: Image Communication, 2020; 84: 115810. doi: 10.1016/j.image.2020.115810.
Ma Y, Zhang W Q, Qureshi W S, Gao C, Zhang C L, Li W. Autonomous navigation for a wolfberry picking robot using visual cues and fuzzy control. Information Processing in Agriculture, 2020; 8(1): 15–26.
Yang S J, Mei S L, Zhang Y N. Detection of maize navigation centerline based on machine vision. IFAC-PapersOnLine, 2018; 51(17): 570–575.
Si Y S, Jiang G Q, Liu G, Gao R, Liu Z X. Early stage crop rows detection based on least square method. Transactions of the Chinese Society of Agricultural Machinery, 2010; 41(7): 163–167, 185. (in Chinese)
Hu L, Luo X W, Zhang Z G, Chen X F, Lin C X. Side-shift offset identification and control of crop row tracking for intra-row mechanical weeding. Transactions of the CSAE, 2013; 29(14): 8–14. (in Chinese)
Zhang R J, Li M Z, Zhang M, Liu G. Rapid crop-row detection based on improved Hough transformation. Transactions of the Chinese Society for Agricultural Machinery, 2009; 40(7): 163–166. (in Chinese)
Mochizuki Y, Torii A, Imiya A. N-Point Hough transform for line detection. Journal of Visual Communication and Image Representation, 2009; 20(4): 242–253.
Mukhopadhyay P, Chaudhuri B B. A survey of Hough Transform. Pattern Recognition, 2015, 48(3): 993–1010.
Vera E, Lucio D, Fernandes L A F, Velho L. Hough Transform for real-time plane detection in depth images. Pattern Recognition Letters, 2018; 103: 8–15.
Barawid O C, Mizushima A, Ishii K, Noguchi N. Development of an Autonomous Navigation System using a Two-dimensional Laser Scanner in an Orchard Application. Biosystems Engineering, 2007; 96(2): 139–149.
Chen Z W, Li W, Zhang W Q, Li Y W, Li M S, Li H. Vegetable crop row extraction method based on accumulation threshold of Hough Transformation. Transactions of the CSAE, 2019; 35(22): 314–322. (in Chinese)
Chen J Q, Qiang H, Wu J H, Xu G W, Wang Z K. Navigation path extraction for greenhouse cucumber-picking robots using the prediction-point Hough transform. Computers and Electronics in Agriculture, 2021; 180: 105911. doi: 10.1016/j.compag.2020.105911.
Li Y, Gans N R. Predictive RANSAC: Effective model fitting and tracking approach under heavy noise and outliers. Computer Vision and Image Understanding, 2017; 161: 99–113.
Zhou S Z, Kang F , Li W B, Kan J M, Zheng Y J, He G J. Extracting diameter at breast height with a handheld mobile LiDAR system in an outdoor environment. Sensors (Basel, Switzerland), 2019; 19(14): 3212. doi: 10.3390/s19143212.
Zhu R J, Zhu Y H, Wang L, Lu W, Luo H, Zhang Z C. Cotton positioning technique based on binocular vision with implementation of scale-invariant feature transform algorithm. Transactions of the CSAE, 2016; 32(6): 182–188. (in Chinese).
Sun Q, Zhang Y, Wang J G, Gao W. An improved FAST feature extraction based on RANSAC method of vision/SINS integrated navigation system in GNSS-denied environments. Advances in Space Research, 2017; 60(12): 2660–2671.
Bochtis D, Griepentrog H W, Vougioukas S, Busato P, Beruto R, Zhou K. Route planning for orchard operations. Computers and Electronics in Agriculture, 2015; 113: 51–60.
Li Y, Ding W L, Zhang X G, Ju Z J. Road detection algorithm for Autonomous Navigation Systems based on dark channel prior and vanishing point in complex road scenes. Robotics and Autonomous Systems, 2016; 85: 1–11.
Narayan A, Tuci E, Labrosse F, Alkilabi M H M. A dynamic colour perception system for autonomous robot navigation on unmarked roads. Neurocomputing, 2018; 275: 2251–2263.
Li J B, Zhu R G, Chen B Q. Image detection and verification of visual navigation route during cotton field management period period. Int J Agric & Biol Eng, 2018; 11(6): 159–165.
Radcliffe J, Cox J, Bulanon D M. Machine vision for orchard navigation. Computers in Industry, 2018; 98: 165–17
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