Zobrazeno 1 - 10
of 56
pro vyhledávání: '"Hwangbo, Jemin"'
Autor:
Yang, Insung, Hwangbo, Jemin
In this research, we investigated the innovative use of a manipulator as a tail in quadruped robots to augment their physical capabilities. Previous studies have primarily focused on enhancing various abilities by attaching robotic tails that functio
Externí odkaz:
http://arxiv.org/abs/2407.10420
Autor:
Kim, Yunho, Lee, Jeong Hyun, Lee, Choongin, Mun, Juhyeok, Youm, Donghoon, Park, Jeongsoo, Hwangbo, Jemin
For reliable autonomous robot navigation in urban settings, the robot must have the ability to identify semantically traversable terrains in the image based on the semantic understanding of the scene. This reasoning ability is based on semantic trave
Externí odkaz:
http://arxiv.org/abs/2406.02989
Legged Robot State Estimation With Invariant Extended Kalman Filter Using Neural Measurement Network
This paper introduces a novel proprioceptive state estimator for legged robots that combines model-based filters and deep neural networks. Recent studies have shown that neural networks such as multi-layer perceptron or recurrent neural networks can
Externí odkaz:
http://arxiv.org/abs/2402.00366
Control of legged robots is a challenging problem that has been investigated by different approaches, such as model-based control and learning algorithms. This work proposes a novel Imitating and Finetuning Model Predictive Control (IFM) framework to
Externí odkaz:
http://arxiv.org/abs/2311.02304
Autor:
Zhang, Hui, Christen, Sammy, Fan, Zicong, Zheng, Luocheng, Hwangbo, Jemin, Song, Jie, Hilliges, Otmar
We present ArtiGrasp, a novel method to synthesize bi-manual hand-object interactions that include grasping and articulation. This task is challenging due to the diversity of the global wrist motions and the precise finger control that are necessary
Externí odkaz:
http://arxiv.org/abs/2309.03891
In the realm of autonomous mobile robots, safe navigation through unpaved outdoor environments remains a challenging task. Due to the high-dimensional nature of sensor data, extracting relevant information becomes a complex problem, which hinders ade
Externí odkaz:
http://arxiv.org/abs/2309.02745
We propose a learning-based system for enabling quadrupedal robots to manipulate large, heavy objects using their whole body. Our system is based on a hierarchical control strategy that uses the deep latent variable embedding which captures manipulat
Externí odkaz:
http://arxiv.org/abs/2308.16820
Autor:
Kim, Yunho, Oh, Hyunsik, Lee, Jeonghyun, Choi, Jinhyeok, Ji, Gwanghyeon, Jung, Moonkyu, Youm, Donghoon, Hwangbo, Jemin
Several earlier studies have shown impressive control performance in complex robotic systems by designing the controller using a neural network and training it with model-free reinforcement learning. However, these outstanding controllers with natura
Externí odkaz:
http://arxiv.org/abs/2308.12517
In this work, a non-gaited framework for legged system locomotion is presented. The approach decouples the gait sequence optimization by considering the problem as a decision-making process. The redefined contact sequence problem is solved by utilizi
Externí odkaz:
http://arxiv.org/abs/2205.14277
For autonomous quadruped robot navigation in various complex environments, a typical SOTA system is composed of four main modules -- mapper, global planner, local planner, and command-tracking controller -- in a hierarchical manner. In this paper, we
Externí odkaz:
http://arxiv.org/abs/2204.08647