Hola,
¿eres nuevo aquí?

Regístrate gratis y conecta tu empresa con financiación pública, partners y proyectos.

Tengo cuenta

Regístrate

Ver video

AssemblySkills

Financiado

Cerrado

Acquiring assembly skills by robot learning

Present-day industrial robots are made for the purpose of repeating several tasks thousands of times. What the manufacturing industry needs instead is a robot that can do thousands of tasks, a few times. Programming a robot to sol... ver más

30/06/2022

TECHNISCHE UNIVERS...

150K€

Presupuesto del proyecto: 150K€

Líder del proyecto

TECHNISCHE UNIVERSITAT DARMSTADT No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 2 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2022-06-30

ERC-2020-POC: Call for proposals for ERC Proof of...

I+D

Cerrada hace 5 años

0% 100% 100%

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

2 Participantes

TECHNISCHE UNIVERSITAT DARMS...

150.00K€ | Lider

ORONA SDAD COOP LTDA

1.05M€ | Participante

Conecta tu I+D

¿Tienes un proyecto y buscas un partner? Gracias a nuestro motor inteligente podemos recomendarte los mejores socios y ponerte en contacto con ellos. Te lo explicamos en este video

Proyectos interesantes

SAHR Skill Acquisition in Humans and Robots 2M€ Cerrado

TERI Teaching Robots Interactively 1M€ Cerrado

ROSETTA RObot control for Skilled ExecuTion of Tasks in natural inte... 10M€ Cerrado

DARWIN Dextrous Assembler Robot Working with embodied INtelligence 4M€ Cerrado

DESARROLLO DE TECNOLOGÍA ROBÓTICA CON CAPACID... DESARROLLO DE TECNOLOGÍA ROBÓTICA CON CAPACIDAD DE APRENDIZA... 357K€ Cerrado

PID2021-126220OB-I00 REPRESENTACION EN APRENDIZAJE CONTINUO Y ABIERTO EN ROBOTS I... 211K€ Cerrado

Duración del proyecto: 19 meses Fecha Inicio: 2020-11-18
Fecha Fin: 2022-06-30

Líder del proyecto

TECHNISCHE UNIVERSITAT DARMSTADT No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 150K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Present-day industrial robots are made for the purpose of repeating several tasks thousands of times. What the manufacturing industry needs instead is a robot that can do thousands of tasks, a few times. Programming a robot to solve just one complex motor task has remained a challenging, costly and time-consuming task. In fact, it has become the key bottleneck in industrial robotics. Empowering robots with the ability to autonomously learn such tasks is a promising approach, and, in theory, machine learning has promised fully adaptive control algorithms which learn both by observation and trial-and-error. However, to date, learning techniques have yet to fulfil this promise, as only few methods manage to scale into the high-dimensional domains of manipulator robotics, or even the new upcoming trend of collaborative robots. The goal of the AssemblySkills ERC PoC is to validate an autonomous skill learning system that enables industrial robots to acquire and improve a rich set of motor skills. Using structured, modular control architectures is a promising concept to scale robot learning to more complex real-world tasks. In such a modular control architecture, elemental building blocks – called movement primitives, need to be adapted, sequenced or co-activated simultaneously. Within the ERC PoC AssemblySkills, our goal is to group these modules into an industry-scale complete software package that can enable industrial robots to learn new skills (particularly in assembly tasks). The value proposition of our ERC PoC is a cost-effective, novel machine learning system that can unlock the potential of manufacturing robots by enabling them to learn to select, adapt and sequence parametrized building blocks such as movement primitives. Our approach is unique in the sense that it can acquire more than just a single desired trajectory as done in competing approaches, capable of save policy adaptation, requires only little data and can explain the solution to the robot operator.

Conecta tu I+D

Entra hoy

¿Olvidé mi contraseña?

Financiación

Empresas

CTIs/Universidades

Proyectos

Investigadores