Roombots-Mechanical Design of Self-Reconfiguring Modular Robots for Adaptive Furniture

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Correspondence functors and duality

Jacques Thévenaz, Serge Bouc

A correspondence functor is a functor from the category of finite sets and correspondences to the category of k-modules, where k is a commutative ring. By means of a suitably defined duality, new correspondence functors are constructed, having remarkable p ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Interlocking modular microfluidic cooling substrates for future high energy physics experiments

Massimo Angeletti

In high energy physics, semiconductor-based sensors are widely used in particle tracking applications. These sensors are typically glued on low-mass cooling substrates, which guarantee the correct thermal management and, at the same time, minimise their in ...

EPFL2023

Integration of feedforward and feedback control in the neuromechanics of vertebrate locomotion: a review of experimental, simulation and robotic studies

Auke Ijspeert

Animal locomotion is the result of complex and multi-layered interactions between the nervous system, the musculo-skeletal system and the environment. Decoding the underlying mechanisms requires an integrative approach. Comparative experimental biology has ...

Company Biologists Ltd2023

Smell Driven Navigation for Soft Robotic Arms: Artificial Nose and Control

Josephine Anna Eleanor Hughes, Francesco Stella

Elephants and other animals heavily rely on the sense of smell to operate. Soft robots would also benefit from an artificial sense of smell, which could be helpful in typical soft robotic tasks such as search and rescue, pipe inspection, and all the tasks ...

IEEE2023

Learning and optimization of anticipatory feedback controllers for robot manipulation

Hakan Girgin

Programming intelligent robots requires robust controllers that can achieve desired tasks while adapting to the changes in the task and the environment. In this thesis, we address the challenges in designing such adaptive and anticipatory feedback controll ...

EPFL2023

The neuromechanics of animal locomotion: From biology to robotics and back

Auke Ijspeert, Pavan P Ramdya

Robotics and neuroscience are sister disciplines that both aim to understand how agile, efficient, and robust locomotion can be achieved in autonomous agents. Robotics has already benefitted from neuromechanical principles discovered by investigating anima ...

AMER ASSOC ADVANCEMENT SCIENCE2023

The science of soft robot design: A review of motivations, methods and enabling technologies

Josephine Anna Eleanor Hughes, Francesco Stella

Novel technologies, fabrication methods, controllers and computational methods are rapidly advancing the capabilities of soft robotics. This is creating the need for design techniques and methodologies that are suited for the multi-disciplinary nature of s ...

FRONTIERS MEDIA SA2023

Identification of the trade-off between speed and efficiency in undulatory swimming using a bio-inspired robot

Auke Ijspeert, Karen Ann J Mulleners, Kamilo Andres Melo Becerra, Laura Isabel Paez Coy, Alexandros Anastasiadis

Anguilliform swimmers, like eels or lampreys, are highly efficient swimmers. Key to understanding their performances is the relationship between the body’s kinematics and resulting swimming speed and efficiency. But, we cannot prescribe kinematics to livin ...

Nature Research2023

Accessible Soft Robotics Education with Re-configurable Balloon Robots

Josephine Anna Eleanor Hughes, Kieran Daniel Gilday, Yi-Shiun Wu

Soft robotics requires effective tools to educate the next generation of engineers and researchers. Stemming from a lack of universally accepted principles for education and with high barriers to entry in terms of fabrication and hardware, education to dat ...

IEEE2023

A Provably Stable Iterative Learning Controller for Continuum Soft Robots

Josephine Anna Eleanor Hughes, Francesco Stella

Fully exploiting soft robots' capabilities requires devising strategies that can accurately control their movements with the limited amount of control sources available. This task is challenging for reasons including the hard-to-model dynamics, the system' ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Identifying important sensory feedback for learning locomotion skills

Auke Ijspeert, Guillaume Denis Antoine Bellegarda, Milad Shafiee Ashtiani

Robot motor skills can be acquired by deep reinforcement learning as neural networks to reflect state-action mapping. The selection of states has been demonstrated to be crucial for successful robot motor learning. However, because of the complexity of neu ...

NATURE PORTFOLIO2023

Investigating the roles of reflexes and central pattern generators in the control and modulation of human locomotion using a physiologically plausible neuromechanical model

Auke Ijspeert, Andrea Di Russo, Dimitar Yuriev Stanev

Objective. Studying the neural components regulating movement in human locomotion is obstructed by the inability to perform invasive experimental recording in the human neural circuits. Neuromechanical simulations can provide insights by modeling the locom ...

Iop Publishing Ltd2023