Project description
The march of the autonomous microbots
From individual receptors and organelles to cells and multi-cellular organisms, nature's living biological matter can sense the environment and respond to it intelligently to get its work accomplished. In many of these systems, the processing of environmental information results in mechanical motion. Scientists have made significant progress toward systems that mimic nature's unique capabilities, yet truly autonomous control has been elusive. The EU-funded MAPEI project will leverage advances in machine learning and embodied intelligence (intelligent behaviour coupling an agent, its environment, perception and motion) to demonstrate intelligent autonomous microbots consisting of microscopic active particles.
Objective
Over billions of years of evolution, motile organisms have developed complex strategies to survive and thrive. These strategies integrate three components: sensors, actuators, and information processing. In the last two decades, active-matter research has tried to replicate the evolutionary success of microorganisms in artificial systems. Researchers have replicated the actuators by developing artificial active particles that extract energy from their environment to perform mechanical work and, to a lesser extent, the sensors, by making these active particles adjust their motion properties to physical cues. However, these artificial particles are still largely incapable of autonomous information processing, which is limiting the scientific insight and technological applications of active matter. The main challenges are: 1. Make active particles capable of autonomous information processing. 2. Optimize the behavioral strategies of individual active particles. 3. Optimize the interactions between active particles. Drawing inspiration from Nature, this project will take the next steps in the evolution of artificial active matter systems by endowing them with embodied intelligence and autonomous information processing abilities. Specifically, it will: 1. Realize microscopic active particles with embodied intelligence (microbots). 2. Use embodied intelligence to achieve optimal behaviors for the microbots. 3. Use embodied intelligence to engineer interactions between microbots. I will achieve this by combining my background in mesoscopic physics and microfabrication with machine learning, a new research direction that offers radically different and complementary opportunities. This project will provide scientific insight into far-from-equilibrium physics and lay the foundations for ground-breaking applications empowered by microbots that are able to autonomously sense and react to their microscopic environment.
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.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors
- natural sciences biological sciences microbiology
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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.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
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.
ERC-COG - Consolidator Grant
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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) ERC-2020-COG
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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.
405 30 Goeteborg
Sweden
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.