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Di An

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Proceedings Article | 4 June 2022 Presentation + Paper

Smart Bi-eBikes (SBB): a low cost UGV solution for precision agriculture applications

Di An, Haoyu Niu, Levi Williams, YangQuan Chen

Proceedings Volume 12114, 121140C (2022) https://doi.org/10.1117/12.2618728

KEYWORDS: Agriculture, Image segmentation, Roads, Unmanned aerial vehicles, Image processing, Evolutionary algorithms, Brain, Actuators, Navigation systems, Unmanned ground vehicles

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Crop pest management has vast economic consequences vital to agricultural, natural lands, and even public health. In this work, we contribute a new low-cost UGV (unmanned ground vehicle) solution to solve this precision agriculture problem. This UGV is made of two electric bikes (bi-eBike) that are commercially off the shelves (COTS) and driven by a ROS (robotics operational system) compatible UGV. Our bi-eBike system offers a mobile platform that can be used as a mobile sensing service with multiple sensors such as multispectral cameras, microwave scanners, etc., as well as a mobile actuation/application service with actuators such as UV-C light insecticide, beneficial bugs, growth stimulant spreaders or sprayers, etc. By mapping and imaging plants in the field, farmers can treat individual plants instead of troubleshooting the entire field, reducing both their costs and negative environmental impact. This smart bi-eBike system can be supplemented with solar panels (photovoltaic) and a UAV (unmanned aircraft vehicle) landing/charging pad. Thus, one can expect that the SBB can have a long operational duration (10 hours or more) and large coverage of acreages where UAVs are used for variability mapping for site-specific treatment. This paper describes the system level concept, subsystem designs and integration, vehicle control electronics, autonomous navigation architecture, and some preliminary experimental results.

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