no code implementations • 15 Mar 2024 • Carmelo Sferrazza, Dun-Ming Huang, Xingyu Lin, Youngwoon Lee, Pieter Abbeel
Humanoid robots hold great promise in assisting humans in diverse environments and tasks, due to their flexibility and adaptability leveraging human-like morphology.
no code implementations • 2 Nov 2023 • Carmelo Sferrazza, Younggyo Seo, Hao liu, Youngwoon Lee, Pieter Abbeel
For tasks requiring object manipulation, we seamlessly and effectively exploit the complementarity of our senses of vision and touch.
1 code implementation • 23 Aug 2023 • Ademi Adeniji, Amber Xie, Carmelo Sferrazza, Younggyo Seo, Stephen James, Pieter Abbeel
Using learned reward functions (LRFs) as a means to solve sparse-reward reinforcement learning (RL) tasks has yielded some steady progress in task-complexity through the years.
3 code implementations • 6 Feb 2023 • Hao liu, Carmelo Sferrazza, Pieter Abbeel
Applying our method to large language models, we observed that Chain of Hindsight significantly surpasses previous methods in aligning language models with human preferences.
no code implementations • 23 Sep 2021 • Pietro Griffa, Carmelo Sferrazza, Raffaello D'Andrea
Grasping objects whose physical properties are unknown is still a great challenge in robotics.
no code implementations • 7 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.
no code implementations • 21 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.
no code implementations • 11 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
no code implementations • 5 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.
no code implementations • 31 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.
no code implementations • 19 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.