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Concept

Self-reconfiguring modular robot

Publications associées (31)

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

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

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

Human Interactive Robotic Surfaces for Physical Immersion

Fabio Zuliani

Computers have long been augmenting human capabilities and communication, and with emerging technologies, physical immersion in virtual worlds is now attainable. These advancements push the boundaries of human potential, allowing designers, architects, eng ...

EPFL2023

Sensorless force and displacement estimation in soft actuators

Jamie Paik, Sagar Dattatray Joshi

Sensing forms an integral part of soft matter based robots due to their compliance, dependence on loading conditions, and virtually infinite degrees of freedom. Previous studies have developed several extrinsic sensors and embedded them into soft actuators ...

ROYAL SOC CHEMISTRY2023

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

Geometric Algebra for Optimal Control With Applications in Manipulation Tasks

Sylvain Calinon, Tobias Löw

Many problems in robotics are fundamentally problems of geometry, which have led to an increased research effort in geometric methods for robotics in recent years. The results were algorithms using the various frameworks of screw theory, Lie algebra, and d ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

A Stable Adaptive Extended Kalman Filter for Estimating Robot Manipulators Link Velocity and Acceleration

Aude Billard, Harshit Khurana

One can estimate the velocity and acceleration of robot manipulators by utilizing nonlinear observers. This involves combining inertial measurement units (IMUs) with the motor encoders of the robot through a model-based sensor fusion technique. This approa ...

IEEE2023

Haptics based multi-level collaborative steering control for automated driving

Hannes Bleuler, Jürg Alexander Schiffmann, Robert Fuchs, Tomohiro Nakade

Increasing the capability of automated driving vehicles is motivated by environmental, productivity, and traffic safety benefits. But over-reliance on the automation system is known to cause accidents. The role of the driver cannot be underestimated as it ...

2023

Colloidal self-assembly of soft neural interfaces from injectable photovoltaic microdevices

Mahmut Selman Sakar, Zhangjun Huang, Murat Kaynak, Haiyan Jia

Biomimetic retinas with a wide field of view and high resolution are in demand for neuroprosthetics and robot vision. Conventional neural prostheses are manufactured outside the application area and implanted as a complete device using invasive surgery. He ...

2023

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