Abstract
Over the recent years, agricultural mobile robots have been an important topic for scientists and for the world of industry. The rapid progress of communication, sensor, and computing technologies has led to a significant increase in the field of guidance systems for autonomous agricultural robots. Agricultural robots that are automated decrease labor expenses, avoid farmers from performing different tasks, and give them reliable, up-to-date data to aid in management choices. This paper provides and discusses a description of the navigation mechanism for the “FellahBot” micro-tractor developed by FellahTech. Navigation sensors, computational methods, and navigation control algorithms are the essential components. Crucial operations include selecting, coordinating, and combining the most suitable sensors to provide the essential data needed for the robot’s navigation. In order to achieve improved localization and map**, image processing and multi-data sensor fusion employ powerful algorithms. Its lines of research are grouped under the name simultaneous localization and map** (SLAM) algorithms. This scientific work aims to evaluate SLAM systems embedded on the architecture CPU-GPU of the Jetson Nano, and we compare with two implementations of Cartographer SLAM and EKF algorithms.
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References
Abouzahir M (2017) Algorithmes SLAM: vers une implémentation embarquée. 2017. Thèse de doctorat. Université Paris Saclay (COmUE); Université Ibn Zohr (Agadir)
Aghi D, Mazzia V, Chiaberge M (2020) Local motion planner for autonomous navigation in vineyards with a RGB-D camera-based algorithm and deep learning synergy. Machines 8(2):27
Concha A and Civera J (2015) DPPTAM: dense piecewise planar tracking and map** from a monocular sequence. In: 2015 IEEE/RSJ international conference on intelligent robots and systems (IROS). IEEE, pp 5686–5693
Engel J, Schöps T, Cremers D (2014) LSD-SLAM: large-scale direct monocular SLAM. European conference on computer vision. Springer, Cham, pp 834–849
Engel J, Koltun V, Cremers D (2017) Direct sparse odometry. IEEE Trans Pattern Anal Mach Intell 40(3):611–625
Forster C, Pizzoli M, Scaramuzza D (2014) SVO: fast semi-direct monocular visual odometry. In: IEEE international conference on robotics and automation (ICRA). IEEE, pp 15–22
Fuentes-Pacheco J, Ruiz-ascencio J, Rendón-mancha JM (2015) Visual simultaneous localization and map**: a survey. Artif Intell Rev 43(1):55–81
Grisetti G, Stachniss C, Burgard W (2007) Improved techniques for grid map** with Rao-blackwellized particle filters. IEEE Trans Robot 23(1):34–46
Guerrouj FZ, Abouzahir M, Ramzi M et al (2021) Analysis of the acceleration of deep learning inference models on a heterogeneous architecture based on OpenVINO. In: 2021 4th international symposium on advanced electrical and communication technologies (ISAECT), IEEE, pp 01–05
Hess W, Kohler D, Rapp H (2016) Real-time loop closure in 2D LIDAR SLAM. In: IEEE international conference on robotics and automation (ICRA). IEEE, pp 1271–1278
Jiang G, Wang Z, Liu H, (2015) Automatic detection of crop rows based on multi-ROIs. Expert Syst Appl 42(5):2429–2441
Klein G and Murray D (2007) Parallel tracking and map** for small AR workspaces. In: 6th IEEE and ACM international symposium on mixed and augmented reality. IEEE, pp 225–234
Kohlbrecher S, Von Stryk O, Meyer J (2011) A flexible and scalable SLAM system with full 3D motion estimation. In: et al IEEE international symposium on safety, security, and rescue robotics. IEEE, pp 155–160
Labbe M, Michaud F (2014) Online global loop closure detection for large-scale multi-session graph-based SLAM. In: 2014 IEEE/RSJ international conference on intelligent robots and systems. IEEE, pp 2661–2666
Moore T, Stouch D (2016) A generalized extended Kalman filter implementation for the robot operating system. Intelligent autonomous systems, vol 13. Springer, Cham, pp 335–348
Mur-artal R, Montiel J, Maria M, Tardos JD (2015) ORB-SLAM: a versatile and accurate monocular SLAM system. IEEE Trans Robot 31(5):1147–1163
Nguyen D-D (2018) A vision system based real-time SLAM applications. Université Paris-Saclay (ComUE), Thèse de doctorat
Pire T, Fischer T, Castro G et al (2017) S-PTAM: stereo parallel tracking and map**. Robot Autonomous Syst 93:27–42
Redmon J, Divvala S, Girshick R et al (2016) You only look once: unified, real-time object detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 779–788
Romeo J, Pajares G, Montalvo M et al (2012) Crop row detection in maize fields inspired on the human visual perception. Sci World J vol 2012
Ronghua JI, Qi L (2011) Crop-row detection algorithm based on random hough transformation. Mathemat Comput Modell 54(3–4):1016–1020
Rovira-Más F, Zhang Q, Reid JF et al (2005) Hough-transform-based vision algorithm for crop row detection of an automated agricultural vehicle. Proc Inst Mech Eng Part D: J Aut Eng 219(8):999–1010
Shamshiri R, Weltzien C, Hameed IA et al (2018) Research and development in agricultural robotics: a perspective of digital farming
Siegwart R, Nourbakhsh IR, Scaramuzza D (2011) Introduction to autonomous mobile robots. MIT Press
Thrun S (2002) Probabilistic robotics. Commun ACM 45(3):52–57
Acknowledgements
We would like to express our gratitude to the Moroccan National Center for Scientific and Technical Research (CNRST) for its encouragement as well as for its financial support (grant number: 37 UM5R2022) during the period June 2022 to April 2023, and a special thanks also to the CEOs of FellahTech and Scube Companies presented by EL BIKRI Réda Amine and HOUNDEKINDO RHYS, respectively, for all their support during my final graduation project of my master’s thesis (March 2021 to June 2021). Finally, I would like to extend my sincere appreciation to my colleagues at FellahTech, especially Jérémie NTCHOUALA and Karima ASSILI, for their collaboration and support.
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Mailka, H., Abouzahir, M., Ramzi, M. (2024). An Outdoor Navigation System Dedicated to a Moroccan Micro-tractor Based on SLAM Algorithms and Multi-sensor Fusion. In: Bendaoud, M., El Fathi, A., Bakhsh, F.I., Pierluigi, S. (eds) Advances in Control Power Systems and Emerging Technologies. ICESA 2023. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-031-51796-9_24
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