Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Si, Zilin"'
Dexterous robotic manipulation remains a challenging domain due to its strict demands for precision and robustness on both hardware and software. While dexterous robotic hands have demonstrated remarkable capabilities in complex tasks, efficiently le
Externí odkaz:
http://arxiv.org/abs/2405.18804
We introduce DIFFTACTILE, a physics-based differentiable tactile simulation system designed to enhance robotic manipulation with dense and physically accurate tactile feedback. In contrast to prior tactile simulators which primarily focus on manipula
Externí odkaz:
http://arxiv.org/abs/2403.08716
Dexterous robotic manipulation in unstructured environments can aid in everyday tasks such as cleaning and caretaking. Anthropomorphic robotic hands are highly dexterous and theoretically well-suited for working in human domains, but their complex de
Externí odkaz:
http://arxiv.org/abs/2310.05266
Tactile sensing is essential for robots to perceive and react to the environment. However, it remains a challenge to make large-scale and flexible tactile skins on robots. Industrial machine knitting provides solutions to manufacture customizable fab
Externí odkaz:
http://arxiv.org/abs/2303.02858
We present MidasTouch, a tactile perception system for online global localization of a vision-based touch sensor sliding on an object surface. This framework takes in posed tactile images over time, and outputs an evolving distribution of sensor pose
Externí odkaz:
http://arxiv.org/abs/2210.14210
Robot simulation has been an essential tool for data-driven manipulation tasks. However, most existing simulation frameworks lack either efficient and accurate models of physical interactions with tactile sensors or realistic tactile simulation. This
Externí odkaz:
http://arxiv.org/abs/2208.02885
Autor:
Gao, Ruohan, Si, Zilin, Chang, Yen-Yu, Clarke, Samuel, Bohg, Jeannette, Fei-Fei, Li, Yuan, Wenzhen, Wu, Jiajun
Objects play a crucial role in our everyday activities. Though multisensory object-centric learning has shown great potential lately, the modeling of objects in prior work is rather unrealistic. ObjectFolder 1.0 is a recent dataset that introduces 10
Externí odkaz:
http://arxiv.org/abs/2204.02389
Knowledge of 3-D object shape is of great importance to robot manipulation tasks, but may not be readily available in unstructured environments. While vision is often occluded during robot-object interaction, high-resolution tactile sensors can give
Externí odkaz:
http://arxiv.org/abs/2109.09884
Autor:
Si, Zilin, Yuan, Wenzhen
Simulation is widely used in robotics for system verification and large-scale data collection. However, simulating sensors, including tactile sensors, has been a long-standing challenge. In this paper, we propose Taxim, a realistic and high-speed sim
Externí odkaz:
http://arxiv.org/abs/2109.04027
Rotational displacement about the grasping point is a common grasp failure when an object is grasped at a location away from its center of gravity. Tactile sensors with soft surfaces, such as GelSight sensors, can detect the rotation patterns on the
Externí odkaz:
http://arxiv.org/abs/2108.00301