Under canopy light detection and ranging–based autonomous navigation

Higuti, Vitor A. H.; Velasquez, Andres E. B.; Magalhaes, Daniel Varela; Becker, Marcelo; Chowdhary, Girish

doi:10.1002/rob.21852

Title: Under canopy light detection and ranging–based autonomous navigation

Journal Article · Wed Dec 12 00:00:00 EST 2018 · Journal of Field Robotics

DOI:https://doi.org/10.1002/rob.21852· OSTI ID:1489516

Higuti, Vitor A. H. ^[1]; Velasquez, Andres E. B. ^[1]; Magalhaes, Daniel Varela ^[1]; Becker, Marcelo ^[1]; Chowdhary, Girish ^[2]

Univ. of Sao Paulo, Sao Paulo (Brazil)
Univ. of Illinois at Urbana-Champaign, Urbana, IL (United States)

This study describes a light detection and ranging (LiDAR)–based autonomous navigation system for an ultralightweight ground robot in agricultural fields. The system is designed for reliable navigation under cluttered canopies using only a 2D Hokuyo UTM–30LX LiDAR sensor as the single source for perception. Its purpose is to ensure that the robot can navigate through rows of crops without damaging the plants in narrow row–based and high–leaf–cover semistructured crop plantations, such as corn (Zea mays) and sorghum (Sorghum bicolor). The key contribution of our work is a LiDAR–based navigation algorithm capable of rejecting outlying measurements in the point cloud due to plants in adjacent rows, low–hanging leaf cover or weeds. The algorithm addresses this challenge using a set of heuristics that are designed to filter out outlying measurements in a computationally efficient manner, and linear least squares are applied to estimate within–row distance using the filtered data. Moreover, a crucial step is the estimate validation, which is achieved through a heuristic that grades and validates the fitted row–lines based on current and previous information. The proposed LiDAR–based perception subsystem has been extensively tested in production/breeding corn and sorghum fields. In such variety of highly cluttered real field environments, the robot logged more than 6 km of autonomous run in straight rows. These results demonstrate highly promising advances to LiDAR–based navigation in realistic field environments for small under–canopy robots.

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Research Organization:: Univ. of Illinois at Urbana-Champaign, IL (United States)

Sponsoring Organization:: USDOE Advanced Research Projects Agency - Energy (ARPA-E)

Grant/Contract Number:: AR0000598

OSTI ID:: 1489516

Alternate ID(s):: OSTI ID: 1485530

Journal Information:: Journal of Field Robotics, Vol. 36, Issue 3; ISSN 1556-4959

Publisher:: WileyCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 40 works

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References (44)

Crop rows and weeds detection in maize fields applying a computer vision system based on geometry Guerrero, José Miguel; Ruz, José Jaime; Pajares, Gonzalo Computers and Electronics in Agriculture, Vol. 142 https://doi.org/10.1016/j.compag.2017.09.028	journal	November 2017
Stereo vision and rover navigation software for planetary exploration Goldberg, S. B.; Maimone, M. W.; Matthies, L. 2002 IEEE Aerospace Conference, Proceedings, IEEE Aerospace Conference https://doi.org/10.1109/AERO.2002.1035370	conference	January 2002
Image-based particle filtering for navigation in a semi-structured agricultural environment Hiremath, Santosh; van Evert, Frits K.; Braak, Cajo ter Biosystems Engineering, Vol. 121 https://doi.org/10.1016/j.biosystemseng.2014.02.010	journal	May 2014
Autonomous navigation using a robot platform in a sugar beet field Bakker, Tijmen; van Asselt, Kees; Bontsema, Jan Biosystems Engineering, Vol. 109, Issue 4 https://doi.org/10.1016/j.biosystemseng.2011.05.001	journal	August 2011
Advanced phenotyping and phenotype data analysis for the study of plant growth and development Rahaman, Md. Matiur; Chen, Dijun; Gillani, Zeeshan Frontiers in Plant Science, Vol. 6 https://doi.org/10.3389/fpls.2015.00619	journal	August 2015
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography Fischler, Martin A.; Bolles, Robert C. Communications of the ACM, Vol. 24, Issue 6 https://doi.org/10.1145/358669.358692	journal	June 1981
Row following in pergola structured orchards Bell, Jamie; MacDonald, Bruce A.; Ahn, Ho Seok 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) https://doi.org/10.1109/IROS.2016.7759120	conference	October 2016
Vision based guidance for robot navigation in agriculture English, Andrew; Ross, Patrick; Ball, David 2014 IEEE International Conference on Robotics and Automation (ICRA) https://doi.org/10.1109/ICRA.2014.6907079	conference	May 2014
Tracking Error Learning Control for Precise Mobile Robot Path Tracking in Outdoor Environment Kayacan, Erkan; Chowdhary, Girish Journal of Intelligent & Robotic Systems, Vol. 95, Issue 3-4 https://doi.org/10.1007/s10846-018-0916-3	journal	August 2018
Automatic detection of curved and straight crop rows from images in maize fields García-Santillán, Iván D.; Montalvo, Martín; Guerrero, José M. Biosystems Engineering, Vol. 156 https://doi.org/10.1016/j.biosystemseng.2017.01.013	journal	April 2017
On the design of a low-cost, light-weight, and highly versatile agricultural robot Grimstad, Lars; Pham, Cong D.; Phan, Huynh T. 2015 IEEE International Workshop on Advanced Robotics and its Social Impacts (ARSO) https://doi.org/10.1109/ARSO.2015.7428210	conference	June 2015
Towards unsupervised weed scouting for agricultural robotics Hall, David; Dayoub, Feras; Kulk, Jason 2017 IEEE International Conference on Robotics and Automation (ICRA) https://doi.org/10.1109/ICRA.2017.7989612	conference	May 2017
Development of an Autonomous Navigation System using a Two-dimensional Laser Scanner in an Orchard Application Barawid, Oscar C.; Mizushima, Akira; Ishii, Kazunobu Biosystems Engineering, Vol. 96, Issue 2 https://doi.org/10.1016/j.biosystemseng.2006.10.012	journal	February 2007
Agricultural robots for field operations: Concepts and components Bechar, Avital; Vigneault, Clément Biosystems Engineering, Vol. 149 https://doi.org/10.1016/j.biosystemseng.2016.06.014	journal	September 2016
The Robotanist: A ground-based agricultural robot for high-throughput crop phenotyping Mueller-Sim, Tim; Jenkins, Merritt; Abel, Justin 2017 IEEE International Conference on Robotics and Automation (ICRA) https://doi.org/10.1109/ICRA.2017.7989418	conference	May 2017
Agricultural robots—system analysis and economic feasibility Pedersen, S. M.; Fountas, S.; Have, H. Precision Agriculture, Vol. 7, Issue 4 https://doi.org/10.1007/s11119-006-9014-9	journal	July 2006
Multi-crop-row detection algorithm based on binocular vision Zhai, Zhiqiang; Zhu, Zhongxiang; Du, Yuefeng Biosystems Engineering, Vol. 150 https://doi.org/10.1016/j.biosystemseng.2016.07.009	journal	October 2016
A new recognition of crop row based on its structural parameter model Zhao, Shuailing; Zhang, Zhibin IFAC-PapersOnLine, Vol. 49, Issue 16 https://doi.org/10.1016/j.ifacol.2016.10.079	journal	January 2016
Kalman Filter for Robot Vision: A Survey Chen, S. Y. IEEE Transactions on Industrial Electronics, Vol. 59, Issue 11 https://doi.org/10.1109/TIE.2011.2162714	journal	November 2012
Autonomous maneuvers of a robotic tractor for farming Wang, Hao; Noguchi, Noboru 2016 IEEE/SICE International Symposium on System Integration (SII) https://doi.org/10.1109/SII.2016.7844063	conference	December 2016
3D perception for accurate row following: Methodology and results 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2013) https://doi.org/10.1109/IROS.2013.6697124	conference	November 2013
Self-Contained Autonomous Indoor Flight with Ranging Sensor Navigation Chowdhary, Girish; Sobers, D. Michael; Pravitra, Chintasid Journal of Guidance, Control, and Dynamics, Vol. 35, Issue 6 https://doi.org/10.2514/1.55410	journal	November 2012
Simultaneous localization and mapping: part I Durrant-Whyte, H.; Bailey, T. IEEE Robotics & Automation Magazine, Vol. 13, Issue 2 https://doi.org/10.1109/MRA.2006.1638022	journal	June 2006
Plant Disease Detection by Imaging Sensors – Parallels and Specific Demands for Precision Agriculture and Plant Phenotyping Mahlein, Anne-Katrin Plant Disease, Vol. 100, Issue 2 https://doi.org/10.1094/PDIS-03-15-0340-FE	journal	February 2016
Robot Farmers: Autonomous Orchard Vehicles Help Tree Fruit Production Bergerman, Marcel; Maeta, Silvio M.; Zhang, Ji IEEE Robotics & Automation Magazine, Vol. 22, Issue 1 https://doi.org/10.1109/MRA.2014.2369292	journal	March 2015
Simultaneous localisation and mapping in a complex field environment Lepej, Peter; Rakun, Jurij Biosystems Engineering, Vol. 150 https://doi.org/10.1016/j.biosystemseng.2016.08.004	journal	October 2016
Optimized EIF-SLAM algorithm for precision agriculture mapping based on stems detection Auat Cheein, F.; Steiner, G.; Perez Paina, G. Computers and Electronics in Agriculture, Vol. 78, Issue 2 https://doi.org/10.1016/j.compag.2011.07.007	journal	September 2011
GPS-denied Indoor and Outdoor Monocular Vision Aided Navigation and Control of Unmanned Aircraft: J. Field Robotics Chowdhary, Girish; Johnson, Eric N.; Magree, Daniel Journal of Field Robotics, Vol. 30, Issue 3 https://doi.org/10.1002/rob.21454	journal	March 2013
Laser range finder model for autonomous navigation of a robot in a maize field using a particle filter Hiremath, Santosh A.; van der Heijden, Gerie W. A. M.; van Evert, Frits K. Computers and Electronics in Agriculture, Vol. 100 https://doi.org/10.1016/j.compag.2013.10.005	journal	January 2014
Leader–follower system using two robot tractors to improve work efficiency Zhang, Chi; Noguchi, Noboru; Yang, Liangliang Computers and Electronics in Agriculture, Vol. 121 https://doi.org/10.1016/j.compag.2015.12.015	journal	February 2016
Automatic detection of crop rows based on multi-ROIs Jiang, Guoquan; Wang, Zhiheng; Liu, Hongmin Expert Systems with Applications, Vol. 42, Issue 5 https://doi.org/10.1016/j.eswa.2014.10.033	journal	April 2015
Laser-Aided Inertial Navigation for Self-Contained Autonomous Indoor Flight Sobers, David; Yamaura, Shunsaku; Johnson, Eric AIAA Guidance, Navigation, and Control Conference https://doi.org/10.2514/6.2010-8211	conference	June 2012
Automatic detection of crop rows in maize fields with high weeds pressure Montalvo, M.; Pajares, G.; Guerrero, J. M. Expert Systems with Applications, Vol. 39, Issue 15 https://doi.org/10.1016/j.eswa.2012.02.117	journal	November 2012
Phenomics – technologies to relieve the phenotyping bottleneck Furbank, Robert T.; Tester, Mark Trends in Plant Science, Vol. 16, Issue 12 https://doi.org/10.1016/j.tplants.2011.09.005	journal	December 2011
The development and assessment of the accuracy of an autonomous GPS-based system for intra-row mechanical weed control in row crops Nørremark, M.; Griepentrog, H. W.; Nielsen, J. Biosystems Engineering, Vol. 101, Issue 4 https://doi.org/10.1016/j.biosystemseng.2008.09.007	journal	December 2008
LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments Tang, Jian; Chen, Yuwei; Niu, Xiaoji Sensors, Vol. 15, Issue 7 https://doi.org/10.3390/s150716710	journal	July 2015
Ambient awareness for agricultural robotic vehicles Reina, Giulio; Milella, Annalisa; Rouveure, Raphaël Biosystems Engineering, Vol. 146 https://doi.org/10.1016/j.biosystemseng.2015.12.010	journal	June 2016
The role of GNSS in the navigation strategies of cost-effective agricultural robots Rovira-Más, Francisco; Chatterjee, Ishani; Sáiz-Rubio, Verónica Computers and Electronics in Agriculture, Vol. 112 https://doi.org/10.1016/j.compag.2014.12.017	journal	March 2015
Lights, camera, action: high-throughput plant phenotyping is ready for a close-up Fahlgren, Noah; Gehan, Malia A.; Baxter, Ivan Current Opinion in Plant Biology, Vol. 24 https://doi.org/10.1016/j.pbi.2015.02.006	journal	April 2015
Automatic tractor guidance using carrier-phase differential GPS Bell, Thomas Computers and Electronics in Agriculture, Vol. 25, Issue 1-2 https://doi.org/10.1016/S0168-1699(99)00055-1	journal	January 2000
Inter-row Robot Navigation using 1D Ranging Sensors Troyer, Tyler A.; Pitla, Santosh; Nutter, Ethan IFAC-PapersOnLine, Vol. 49, Issue 16 https://doi.org/10.1016/j.ifacol.2016.10.084	journal	January 2016
Towards a Reliable Monitoring Robot for Mountain Vineyards Santos, Filipe Baptista Neves dos; Sobreira, Heber Miguel Placido; Campos, Daniel Filipe Barros 2015 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC) https://doi.org/10.1109/ICARSC.2015.21	conference	April 2015
Agricultural Robotic Platform with Four Wheel Steering for Weed Detection Bak, Thomas; Jakobsen, Hans Biosystems Engineering, Vol. 87, Issue 2 https://doi.org/10.1016/j.biosystemseng.2003.10.009	journal	February 2004
Study and Experiment on a Wheat Precision Seeding Robot Haibo, Lin; Shuliang, Dong; Zunmin, Liu Journal of Robotics, Vol. 2015 https://doi.org/10.1155/2015/696301	journal	January 2015

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Soft Robotics as an Enabling Technology for Agroforestry Practice and Research Chowdhary, Girish; Gazzola, Mattia; Krishnan, Girish Sustainability, Vol. 11, Issue 23 https://doi.org/10.3390/su11236751	journal	November 2019
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