Descripción del proyecto
Soluciones de inteligencia artificial y robótica para reducir la escasez de mano de obra
En sectores críticos como las energías renovables y la agricultura, el reto consiste en mantener la competitividad en un contexto de creciente escasez de mano de obra. Para salvaguardar industrias vitales, se hace imperativo un cambio sísmico hacia la integración de la inteligencia artificial y la robótica. En este contexto, el equipo del proyecto ARISE, financiado con fondos europeos, introducirá tecnologías de vanguardia que revolucionarán las tareas de manipulación complejas y redefinirán el futuro de la automatización. En concreto, desarrollará manipuladores neumáticos reconfigurables, efectores suaves de rigidez variable y módulos de percepción de vanguardia. Esta innovadora cadena de herramientas, con aplicaciones en tareas de instalación, reparación, trasplante y cosecha en granjas solares e hidropónicas, promete un salto transformador en el panorama de la automatización. En conjunto, el planteamiento integral del proyecto, desde el aprendizaje jerárquico por imitación hasta el despliegue la inteligencia artificial perimetral, anuncia una nueva era de eficiencia y progreso.
Objetivo
Maintaining the competitiveness and leadership position of crucial industries such as renewable energy and agriculture, is contingent upon AI and Robotics increasingly becoming a widespread and integral part of the relevant technological landscapes, particularly in the face of steep labour shortages. ARISE project aims to introduce a combination of perception and control modules around a reconfigurable robotic manipulator that will enable a step change in the level of automation of complex manipulation tasks. ARISE will comprise the following key novel technology components that will significantly push the state of the art in terms of automatic task segmentation, human robot interaction and complex manipulation: (1) Two reconfigurable pneumatic-based robotic manipulators mounted on a mobile robotic platform (2) Novel soft end-effectors with variable stiffness that will allow for a diverse set of manipulation tasks (3) A Robotic perception module comprising 3D vision algorithms (4) A Localisation and Mapping module that will allow the robot to accurately identify its position within the environment (5) A Semantic Mapping module powered by scene understanding algorithms (6) A Knowledge Representation framework that will capture important information regarding objects’ properties and relationships (7) A Hierarchical Imitation Learning framework for acquiring robotic skills to accomplish complex tasks directly from human demonstrators (8) A Human-Interaction conditioned Path and Task planning module enabling reactive robot control (9) An edge-AI framework for deploying Machine Learning models and computer vision algorithms at the edge in a streamlined fashion. The ARISE toolchain will be integrated and validated in 5 real use case scenarios including installation and repair, and transplanting and harvesting tasks, in solar and hydroponic farms, respectively.
Ámbito científico
- engineering and technologyenvironmental engineeringenergy and fuelsrenewable energy
- natural sciencescomputer and information sciencesartificial intelligencecomputer vision
- social sciencessociologyindustrial relationsautomation
- natural sciencescomputer and information sciencesknowledge engineering
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Palabras clave
Programa(s)
Convocatoria de propuestas
HORIZON-CL4-2023-DIGITAL-EMERGING-01
Consulte otros proyectos de esta convocatoriaRégimen de financiación
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinador
15232 Chalandri
Grecia