Project description
Smart robotic system for automated harvesting in agriculture
Food demand is increasing due to the growth of the global population and the challenges posed by climate change, leading agriculture to advanced technology in order to secure quality and quantity of production. Precision agriculture is rising, combined with smart robotic technologies such as smart harvesting that benefit both productivity and working conditions. However, robotic systems are not fully prepared to replace all human actions, thus preventing the transition to fully automated harvesting. The EU-funded BACCHUS project proposes a smart robotic system utilising autonomous mobile platforms with dual manipulators for active inspection and selective harvesting of high value crops, replacing farmer work. The new system will be tested in a vineyard environment monitoring the state of different types of vines and harvesting grapes of different varieties in a human-like manner.
Objective
With the growing population and climate change, agricultural productivity growth is unlikely to meet the increased demand for food. Besides the increasing pressure to produce more, there is an overall need for higher quality and sustainable cultivation. Precision agriculture combined with intelligent robotic technologies can push to that direction. The incorporation of such technologies into agricultural production not only benefits productivity but also improves the working conditions of farmers and labourers. Intelligent systems are becoming the go-to solution to push towards precision agriculture, while a large number of farmer operations are already transitioning to full autonomy. Smart, automated and selective harvesting, in particular, can provide considerable improvement in production leaving the unripe product in the field to mature. However, in order to achieve such automation significant progress is required regarding the cognitive and mechatronic capabilities of the robotic agents replacing the human workers in these tasks, especially in cases where human-like actions are required by the robots. BACCHUS intelligent mobile robotic system promises to reproduce hand harvesting operations, while at the same time take the manual legwork out by autonomously operating in four different levels: i) performing robot navigation with quality performance guarantee in order to inspect the crops and collect data from the agricultural area through embedded sensorial system; ii) performing bi-manual harvesting operations with the needed finesse using a modular robotic platform, iii) employing additive manufacturing for adjusting the robot gripper to the geometry of the different crops, iii) presenting advanced cognitive capabilities and decision making skills. The envisioned system will be demonstrated and evaluated in the challenging vineyard environment inspecting different types of vines and harvesting bunches of grapes of different varieties in a human-like manner.
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: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- agricultural sciences agriculture, forestry, and fisheries agriculture horticulture viticulture
- social sciences sociology industrial relations automation
- social sciences economics and business economics production economics productivity
- engineering and technology mechanical engineering manufacturing engineering additive manufacturing
- natural sciences earth and related environmental sciences atmospheric sciences climatology climatic changes
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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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H2020-EU.2.1.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)
MAIN PROGRAMME
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Topic(s)
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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.
RIA - Research and Innovation action
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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) H2020-ICT-2018-20
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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.
546 36 THESSALONIKI
Greece
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.