Abstract
Currently, an agricultural method called SynecocultureTM has been receiving attention as a means for multiple crop production and recovering from environmental degradation; it helps in regreening the environment and establishing an augmented ecosystem with high biodiversity. In this method, several types of plants are grown densely, and their management relies mainly on manual labor, since conventional agricultural machines and robots cannot be applied in complex vegetation. To improve work efficiency and boost regreening by scaling-up Synecoculture, we developed a robot that can sow, prune, and harvest in dense and diverse vegetation that grows under solar panels, towards the achievement of compatibility between food and energy production on a large scale. We adopted a four-wheel mechanism with sufficient ability to move on uneven terrain, and a two orthogonal axes mechanism with adjusted tool positioning while performing management tasks. In the field experiment, the robot could move straight on shelving slopes and overcome obstacles, such as small steps and weeds, and succeeded in harvesting and weeding with human operation, using the tool maneuver mechanism based on the recognition of the field situation through camera image.
Subject
Plant Science,Agronomy and Crop Science,Food Science
Reference39 articles.
1. Human augmentation of ecosystems: Objectives for food production and science by 2045;Funabashi;NPJ Sci. Food,2018
2. Ohta, K., Kawaoka, T., and Funabashi, M. (2020). Secondary Metabolite Differences between Naturally Grown and Conventional Coarse Green Tea. Agriculture, 10.
3. Brown, J., Colombo, K., Salem, L., Jeng, N., Stothers, R., and Lees, S. (2022, November 01). Polar Coordinate Farm Bot Final Project Report; Industrial and Manufacturing Engineering. Available online: https://digitalcommons.calpoly.edu/cgi/viewcontent.cgi?article=1230&context=imesp.
4. Grimstad, L., and From, J.P. (2017). The Thorvald II Agricultural Robotic System. Robotics, 6.
5. Efficacy of Mechanical Weeding Tools: A Study Into Alternative Weed Management Strategies Enabled by Robotics;McCool;IEEE Robot. Autom. Lett.,2018
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