Efficient Multibody Interactive Simulation for Soft Robotics
The aim of the EMISSR project is to create a novel multibody dynamics simulator for soft robotics. The originality of the
project consists in a unified constraint based formulation that can couple rigid and flexible bodies in the...
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Información proyecto EMISSR
Duración del proyecto: 33 meses
Fecha Inicio: 2018-03-19
Fecha Fin: 2021-01-13
Líder del proyecto
KOBENHAVNS UNIVERSITET
No se ha especificado una descripción o un objeto social para esta compañía.
TRL
4-5
Presupuesto del proyecto
212K€
Fecha límite de participación
Sin fecha límite de participación.
Descripción del proyecto
The aim of the EMISSR project is to create a novel multibody dynamics simulator for soft robotics. The originality of the
project consists in a unified constraint based formulation that can couple rigid and flexible bodies in the same solver. The
argument behind a simulator for soft robotics is the fact that traditional robots are not suitable for working in humans and
their control has proven daunting especially for nonlinear underactuated systems. The new field of soft robotics is seeing
great growth and investment around the globe and Europe needs to seize this economic opportunity. New dynamics
simulations and control algorithms are needed for soft robots, that are made up of soft parts and biology inspired actuators.
EMISSR wants to fill in this gap and aims to become a testbed for training control policies based on machine learning and
other algorithms. In terms of performance and accuracy, EMISSR will be a high-fidelity interactive simulator, meaning that it
will be extremely fast due to its multilevel solver and parallel implementation, while not sacrificing much of the accuracy
needed for soft robotics applications. The frictional contact and deformable continua models will not make any unphysical
approximations. The elements that will distinguish EMISSR from other existing projects are: two-way coupling of rigid and
soft bodies, a fast multilevel iterative solver, stability for high mass ratios and transversal oscillations and robust contact
information generation. These will be applied to making virtual replicas of soft robots (e.g. soft body parts, artificial muscles
and tendons, pneumatic tubes), simulating their dynamics and testing machine learning based control policies for large
numbers of degrees of freedom. At the same time, the training programme that UCPH offers matches my career
development needs perfectly, allowing me to build upon my current competencies, not forgetting the opportunity to enhance
my academic profile and teaching experience.