Search Results for author: Raffaello D'Andrea

Found 9 papers, 0 papers with code

Sample-Efficient Learning to Solve a Real-World Labyrinth Game Using Data-Augmented Model-Based Reinforcement Learning

no code implementations15 Dec 2023 Thomas Bi, Raffaello D'Andrea

Motivated by the challenge of achieving rapid learning in physical environments, this paper presents the development and training of a robotic system designed to navigate and solve a labyrinth game using model-based reinforcement learning techniques.

Model-based Reinforcement Learning Navigate +2

Offset-free Model Predictive Control: A Ball Catching Application with a Spherical Soft Robotic Arm

no code implementations12 Mar 2021 Yaohui Huang, Matthias Hofer, Raffaello D'Andrea

This paper presents an offset-free model predictive controller for fast and accurate control of a spherical soft robotic arm.

Robotics Systems and Control Systems and Control

Zero-shot sim-to-real transfer of tactile control policies for aggressive swing-up manipulation

no code implementations7 Jan 2021 Thomas Bi, Carmelo Sferrazza, Raffaello D'Andrea

This paper aims to show that robots equipped with a vision-based tactile sensor can perform dynamic manipulation tasks without prior knowledge of all the physical attributes of the objects to be manipulated.

Sim-to-real for high-resolution optical tactile sensing: From images to 3D contact force distributions

no code implementations21 Dec 2020 Carmelo Sferrazza, Raffaello D'Andrea

The images captured by vision-based tactile sensors carry information about high-resolution tactile fields, such as the distribution of the contact forces applied to their soft sensing surface.

A Vision-based Sensing Approach for a Spherical Soft Robotic Arm

no code implementations11 Dec 2020 Matthias Hofer, Carmelo Sferrazza, Raffaello D'Andrea

The reliability of the sensing approach is demonstrated by using the sensory feedback to control the orientation of the robotic arm in closed-loop.

Robotics

Learning the sense of touch in simulation: a sim-to-real strategy for vision-based tactile sensing

no code implementations5 Mar 2020 Carmelo Sferrazza, Thomas Bi, Raffaello D'Andrea

Data-driven approaches to tactile sensing aim to overcome the complexity of accurately modeling contact with soft materials.

Towards vision-based robotic skins: a data-driven, multi-camera tactile sensor

no code implementations31 Oct 2019 Camill Trueeb, Carmelo Sferrazza, Raffaello D'Andrea

This paper describes the design of a multi-camera optical tactile sensor that provides information about the contact force distribution applied to its soft surface.

Vision-Based Proprioceptive Sensing for Soft Inflatable Actuators

no code implementations19 Sep 2019 Peter Werner, Matthias Hofer, Carmelo Sferrazza, Raffaello D'Andrea

The resulting sensing pipeline runs at 40 Hz in real-time on a standard laptop and is additionally used for closed loop elongation control of the actuator.

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