Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Gomes, Daniel Fernandes"'
This paper introduces RoTipBot, a novel robotic system for handling thin, flexible objects. Different from previous works that are limited to singulating them using suction cups or soft grippers, RoTipBot can grasp and count multiple layers simultane
Externí odkaz:
http://arxiv.org/abs/2406.09332
Publikováno v:
5th UK Robot Manipulation Workshop 2024
End-to-end self-supervised models have been proposed for estimating the success of future candidate grasps and video predictive models for generating future observations. However, none have yet studied these two strategies side-by-side for addressing
Externí odkaz:
http://arxiv.org/abs/2403.07877
Publikováno v:
Robotics: Science and Systems 2023
Recently, several morphologies, each with its advantages, have been proposed for the \textit{GelSight} high-resolution tactile sensors. However, existing simulation methods are limited to flat-surface sensors, which prevents their usage with the newe
Externí odkaz:
http://arxiv.org/abs/2305.12605
Autor:
Gomes, Daniel Fernandes, Luo, Shan
Tactile sensing is an essential capability for robots that carry out dexterous manipulation tasks. While cameras, Lidars and other remote sensors can assess a scene globally and instantly, tactile sensors can reduce their measurement uncertainties an
Externí odkaz:
http://arxiv.org/abs/2112.01834
Recently simulation methods have been developed for optical tactile sensors to enable the Sim2Real learning, i.e., firstly training models in simulation before deploying them on the real robot. However, some artefacts in the real objects are unpredic
Externí odkaz:
http://arxiv.org/abs/2112.01807
Crack detection is of great significance for monitoring the integrity and well-being of the infrastructure such as bridges and underground pipelines, which are harsh environments for people to access. In recent years, computer vision techniques have
Externí odkaz:
http://arxiv.org/abs/2105.06325
Tactile sensing is important for robots to perceive the world as it captures the texture and hardness of the object in contact and is robust to illumination and colour variances. However, due to the limited sensing area and the resistance of the fixe
Externí odkaz:
http://arxiv.org/abs/2103.00595
Most current works in Sim2Real learning for robotic manipulation tasks leverage camera vision that may be significantly occluded by robot hands during the manipulation. Tactile sensing offers complementary information to vision and can compensate for
Externí odkaz:
http://arxiv.org/abs/2101.07169
Sensing contacts throughout the fingers is an essential capability for a robot to perform manipulation tasks in cluttered environments. However, existing tactile sensors either only have a flat sensing surface or a compliant tip with a limited sensin
Externí odkaz:
http://arxiv.org/abs/2008.05404
Developing autonomous assistants to help with domestic tasks is a vital topic in robotics research. Among these tasks, garment folding is one of them that is still far from being achieved mainly due to the large number of possible configurations that
Externí odkaz:
http://arxiv.org/abs/1907.00408