Zobrazeno 1 - 10
of 191
pro vyhledávání: '"Turk, Greg"'
This paper introduces a novel Lagrangian fluid solver based on covector flow maps. We aim to address the challenges of establishing a robust flow-map solver for incompressible fluids under complex boundary conditions. Our key idea is to use particle
Externí odkaz:
http://arxiv.org/abs/2405.09801
Generative models such as GANs and diffusion models have demonstrated impressive image generation capabilities. Despite these successes, these systems are surprisingly poor at creating images with hands. We propose a novel training framework for gene
Externí odkaz:
http://arxiv.org/abs/2401.15075
Publikováno v:
Proceedings of The 7th Conference on Robot Learning, PMLR 229:2288-2303, 2023
This paper explores the principles for transforming a quadrupedal robot into a guide robot for individuals with visual impairments. A guide robot has great potential to resolve the limited availability of guide animals that are accessible to only two
Externí odkaz:
http://arxiv.org/abs/2306.14055
We present a method for reproducing complex multi-character interactions for physically simulated humanoid characters using deep reinforcement learning. Our method learns control policies for characters that imitate not only individual motions, but a
Externí odkaz:
http://arxiv.org/abs/2305.20041
In-hand object manipulation is challenging to simulate due to complex contact dynamics, non-repetitive finger gaits, and the need to indirectly control unactuated objects. Further adapting a successful manipulation skill to new objects with different
Externí odkaz:
http://arxiv.org/abs/2303.12726
Autor:
Turk, Greg, O'Brien, James F.
Publikováno v:
In Proceedings of ACM SIGGRAPH 1999, pages 335-342, August 1999
Traditionally, shape transformation using implicit functions is performed in two distinct steps: 1) creating two implicit functions, and 2) interpolating between these two functions. We present a new shape transformation method that combines these tw
Externí odkaz:
http://arxiv.org/abs/2303.02937
Text-to-image models, which can generate high-quality images based on textual input, have recently enabled various content-creation tools. Despite significantly affecting a wide range of downstream applications, the distributions of these generated i
Externí odkaz:
http://arxiv.org/abs/2302.03675
The rise of deep learning has caused a paradigm shift in robotics research, favoring methods that require large amounts of data. Unfortunately, it is prohibitively expensive to generate such data sets on a physical platform. Therefore, state-of-the-a
Externí odkaz:
http://arxiv.org/abs/2111.00956
Autor:
Erickson, Zackory, Clever, Henry M., Gangaram, Vamsee, Xing, Eliot, Turk, Greg, Liu, C. Karen, Kemp, Charles C.
Towards the goal of robots performing robust and intelligent physical interactions with people, it is crucial that robots are able to accurately sense the human body, follow trajectories around the body, and track human motion. This study introduces
Externí odkaz:
http://arxiv.org/abs/2105.11582
Contact pressure between the human body and its surroundings has important implications. For example, it plays a role in comfort, safety, posture, and health. We present a method that infers contact pressure between a human body and a mattress from a
Externí odkaz:
http://arxiv.org/abs/2105.09936