Project description
Enabling robots to contextualise underdetermined manipulation task requests
The formidable challenge of creating computational models for versatile manipulation tasks, applicable to any object and purpose, would revolutionise AI and robotics. The ERC-funded FAME project aims to equip robots with a KR&R framework based on machine-interpretable inner-world models, enabling them to contextualise underdetermined manipulation task requests on the first attempt. The project will design, implement, and evaluate the future-orientated cognitive action modelling engine (FAME), a hybrid symbolic/sub-symbolic KR&R framework. The project aims to achieve the modelling and parameterisation of manipulation motion patterns, the ability to mentally simulate imagined and observed manipulation tasks, and the on-demand acquisition of task-specific causal models for novel manipulation tasks through mental physics-based simulations.
Objective
The realization of computational models for accomplishing everyday manipulation tasks for any object and any purpose would be a
disruptive breakthrough in the creation of versatile, general-purpose robot agents; and it is a grand challenge for AI and robotics.
Humans are able to accomplish tasks such as “cut up the fruit” for many types of fruit by generating a large variety of context-specific
manipulation behaviors. They can typically accomplish the tasks on the first attempt despite uncertain physical conditions and novel
objects. Acting so effectively requires comprehensive reasoning about the possible consequences of intended behavior before
physically interacting with the real world.
In the FAME project, I will investigate the research hypothesis that a knowledge representation and reasoning (KR&R) framework
based on explictly-represented and machine-interpretable inner-world models can enable robots to contextualize underdetermined
manipulation task requests on the first attempt. To this end, I will design, implement, and evaluate FAME (Future-oriented cognitive
Action Modelling Engine), a hybrid symbolic/subsymbolic KR&R framework that will contextualize actions by reasoning symbolically
in an abstract and generalized manner but also by reasoning with “one’s eyes and hands” through mental simulation and imagistic
reasoning. Realizing FAME requires three breakthrough research results:
(1) modelling and parameterization of manipulation motion patterns and understanding the resulting effects under
uncertain conditions;
(2) the ability to mentally simulate imagined and observed manipulation tasks to link them to the robot’s knowledge and experience;
and
(3) the on-demand acquisition of task-specific causal models for novel manipulation tasks through mental physics-based simulations.
To assess the power and feasibility of FAME, I will use open manipulation task learning as a benchmark challenge.
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 horticulture fruit growing
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering robotics
You need to log in or register to use this function
We are sorry... an unexpected error occurred during execution.
You need to be authenticated. Your session might have expired.
Thank you for your feedback. You will soon receive an email to confirm the submission. If you have selected to be notified about the reporting status, you will also be contacted when the reporting status will change.
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.
-
HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
See all projects funded under this programme
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-ERC - HORIZON ERC Grants
See all projects funded under this funding scheme
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-2022-ADG
See all projects funded under this callHost institution
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.
28359 Bremen
Germany
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.