Abstract
The Agri.q rover for precision agriculture is the main focus of the present paper. After a description of the prototype, a set of experimental results is presented to validate the energetic sustainability of the robot. Characterized by a modular articulated mechanical structure, and provided with specific sensors and tools, the Agri.q is able to operate in unstructured agricultural environments in order to fulfill several tasks as mapping, monitoring, and manipulating or collecting small soil and crop samples. In addition, the rover is equipped with a platform covered with solar panels, whose orientation can be exploited to maximize the efficiency of the energy harvesting, but also to function as a self-leveling landing platform for drones. The design of such system was mainly driven by a particular attention to energy consumption, bearing in mind the main objective of improving the profitability while decreasing the impact of the agricultural processes. In this paper, all these characteristics are described and analyzed in detail, with particular attention to the energy balance of the whole machine deriving from locomotion on different slopes and soils, panels orienting operations, and of course collection of solar energy.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Gil, J.D.B., Reidsma, P., Giller, K., Todman, L., Whitmore, A., van Ittersum, M.: Sustainable development goal 2: improved targets and indicators for agriculture and food security. Ambio 48(7), 685–698 (2018). https://doi.org/10.1007/s13280-018-1101-4
Vecchio, Y., De Rosa, M., Adinolfi, F., Bartoli, L., Masi, M.: Adoption of precision farming tools: a context-related analysis. Land Use Policy 94, 104481 (2020)
Lowenberg-DeBoer, J., Huang, I.Y., Grigoriadis, V., Blackmore, S.: Economics of robots and automation in field crop production. Precision Agric. 21(2), 278–299 (2019). https://doi.org/10.1007/s11119-019-09667-5
Vecchio, Y., Agnusdei, G.P., Miglietta, P.P., Capitanio, F.: Adoption of precision farming tools: the case of Italian farmers. Int. J. Environ. Res. Public Health 17(3), 869 (2020)
Wang, Y., Lan, Y., Zheng, Y., Lee, K., Cui, S., Lian, J.A.: A UGV-based laser scanner system for measuring tree geometric characteristics. In: International Symposium on Photoelectronic Detection and Imaging 2013: Laser Sensing and Imaging and Applications, vol. 8905, p. 890532. International Society for Optics and Photonics (2013)
Zaman, S., Comba, L., Biglia, A., Aimonino, D.R., Barge, P., Gay, P.: Cost-effective visual odometry system for vehicle motion control in agricultural environments. Comput. Electron. Agric. 162, 82–94 (2019)
Tokekar, P., Vander Hook, J., Mulla, D., Isler, V.: Sensor planning for a symbiotic UAV and UGV system for precision agriculture. IEEE Trans. Robot. 32(6), 1498–1511 (2016)
Khaliq, A., Comba, L., Biglia, A., Ricauda Aimonino, D., Chiaberge, M., Gay, P.: Comparison of satellite and UAV-based multispectral imagery for vineyard variability assessment. Remote Sensing 11(4), 436 (2019)
Chatzimichali, A.P., Georgilas, I.P., Tourassis, V.D.: Design of an advanced prototype robot for white asparagus harvesting. In: 2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, pp. 887–892. IEEE (2009)
Konam, S.: Agricultural aid for mango cutting (AAM). In: 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 1520–1524. IEEE (2014)
Quaglia, G., Visconte, C., Carbonari, L., Botta, A., Cavallone, P.: Agri.q: a sustainable rover for precision agriculture. In: Visa, I., Duta, A. (eds.) Solar Energy Conversion in Communities, pp. 81–91. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-55757-7_6
Cavallone, P., Botta, A., Carbonari, L., Visconte, C., Quaglia, G.: The agri.q mobile robot: preliminary experimental tests. In: Niola, V., Gasparetto, A. (eds.) The International Conference of IFToMM Italy, pp. 524–532. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-55807-9_59
Quaglia, G., Visconte, C., Scimmi, L.S., Melchiorre, M., Cavallone, P., Pastorelli, S.: Robot arm and control architecture integration on a UGV for precision agriculture. In: IFToMM World Congress on Mechanism and Machine Science, pp. 2339–2348. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-20131-9_231
Carbonari, L., Botta, A., Cavallone, P., Tagliavini, L., Quaglia, G.: Data driven analysis of locomotion for a class of articulated mobile robots. J. Mech. Robot. 1–15 (2021)
Visconte, C., Cavallone, P., Carbonari, L., Botta, A., Quaglia, G.: Design of a mechanism with embedded suspension to reconfigure the agri\(\_q\) locomotion layout. Robotics 10(1), 1–14 (2021)
Solar irradiance data (2021). https://solcast.com/
Botta, A., Cavallone, P., Tagliavini, L., Carbonari, L., Visconte, C., Quaglia, G.: An estimator for the kinematic behaviour of a mobile robot subject to large lateral slip. Appl. Sci. 11(4), 1594 (2021)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Botta, A., Cavallone, P. (2022). Robotics Applied to Precision Agriculture: The Sustainable Agri.q Rover Case Study. In: Quaglia, G., Gasparetto, A., Petuya, V., Carbone, G. (eds) Proceedings of I4SDG Workshop 2021. I4SDG 2021. Mechanisms and Machine Science, vol 108. Springer, Cham. https://doi.org/10.1007/978-3-030-87383-7_5
Download citation
DOI: https://doi.org/10.1007/978-3-030-87383-7_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-87382-0
Online ISBN: 978-3-030-87383-7
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)