Project description
AI-driven, solar-powered weeding robot for sustainable farming
Weed management poses significant challenges with conventional methods commonly contributing to soil pollution, CO2 emissions, and hazardous labour conditions. Organic farming faces even greater difficulties due to its reliance on herbicide-free practices. The EIC-funded RoboAIweeder project addresses these issues by developing a fully autonomous, solar-powered and AI-driven weeding robot, suited to the needs of small and medium-sized farmers, particularly those practicing organic farming in Southern Europe, who are struggling the most with affordable weed control. The technology reduces the reliance on herbicides and lowers carbon emissions while simultaneously tackling critical challenges related to labour force availability. It ensures continuous production under extreme weather conditions and, through advanced analytics, enhances productivity and decision-making, boosting the resilience of farming operations.
Objective
Fighting weeds is one of the oldest problems of agriculture. The current solutions include mass use of herbicides, mechanical tilling or manual weeding. Herbicides are poisons which kill not only weeds, pollute the soil, water and bring lasting damage to all living organisms, including health and well-being of humans. Mechanical weeding with standard agri machines (ICE-based) adds to CO2 emissions, damages and compacts soils, and is very imprecise. And manual weeding is back-breaking, often dangerous, low-paid work for which there are fewer and fewer candidates.
Our solution addresses all these environmental, economic and health problems together. It will also strongly support the expansion of organic agriculture in Europe, which is facing much more difficulties with weed pressure, compared to conventional farming. And our innovation is also specifically designed to target the needs of the most climate-vulnerable farmers – those from the semi-mountainous regions of Southern Europe.
We offer a fully automated solution in the form of a 4-wheeled rover, with in-wheel integrated electrical engines, solid X-Y-Z wheel synchronization and front-steering mechanism. It is lightweight and solar-powered for 24-hour working cycle. The robot uses AI based on deep neural networks to spot weeds among desired plants. It can effectively destroy weeds using contact (mechanical) and non-contact (energy beam) methods, depending on both weed size and type, and soil and weather conditions, without creating any fire hazard in the process. Finally, our robot can self-navigate in and around the fields, which is achieved without costly RTK equipment, by combining multi-GNSS (including Galileo) receivers and cameras with proprietary algorithms. The robot has huge potential to expand its capabilities by adding sensors for soil, weather tracking, etc., and we can grow our offer by supplying vast plant and field data analytics and predictive analysis to farmers and other potential clients.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- agricultural sciences agriculture, forestry, and fisheries agriculture sustainable agriculture
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors optical sensors
- natural sciences computer and information sciences artificial intelligence computational intelligence
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.3.1 - The European Innovation Council (EIC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-EIC-ACC-BF - HORIZON EIC Accelerator Blended Finance
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-EIC-2023-ACCELERATOR-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
1784 SOFIA
Bulgaria
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.