Zobrazeno 1 - 10
of 130
pro vyhledávání: '"Choi, Sungjoon"'
Autor:
Yoon, Taerim, Kang, Dongho, Kim, Seungmin, Ahn, Minsung, Cheng, Jin, Coros, Stelian, Choi, Sungjoon
This work introduces a motion retargeting approach for legged robots, which aims to create motion controllers that imitate the fine behavior of animals. Our approach, namely spatio-temporal motion retargeting (STMR), guides imitation learning procedu
Externí odkaz:
http://arxiv.org/abs/2404.11557
In robotic object manipulation, human preferences can often be influenced by the visual attributes of objects, such as color and shape. These properties play a crucial role in operating a robot to interact with objects and align with human intention.
Externí odkaz:
http://arxiv.org/abs/2403.11513
Autor:
Park, Jeongeun, Jeong, Taemoon, Kim, Hyeonseong, Byun, Taehyun, Shin, Seungyoon, Choi, Keunjun, Kwon, Jaewoon, Lee, Taeyoon, Pan, Matthew, Choi, Sungjoon
This paper presents the design and development of an innovative interactive robotic system to enhance audience engagement using character-like personas. Built upon the foundations of persona-driven dialog agents, this work extends the agent applicati
Externí odkaz:
http://arxiv.org/abs/2403.10041
This work presents Past as a Guide (PaG), a simple approach for Large Language Models (LLMs) to improve the coding capabilities by integrating the past history with interactive and iterative code refinements. To be specific, inspired by human cogniti
Externí odkaz:
http://arxiv.org/abs/2311.07635
Pick-and-place is one of the fundamental tasks in robotics research. However, the attention has been mostly focused on the ``pick'' task, leaving the ``place'' task relatively unexplored. In this paper, we address the problem of placing objects in th
Externí odkaz:
http://arxiv.org/abs/2309.13937
Autor:
Park, Jeongeun, Lim, Seungwon, Lee, Joonhyung, Park, Sangbeom, Chang, Minsuk, Yu, Youngjae, Choi, Sungjoon
In this paper, we focus on inferring whether the given user command is clear, ambiguous, or infeasible in the context of interactive robotic agents utilizing large language models (LLMs). To tackle this problem, we first present an uncertainty estima
Externí odkaz:
http://arxiv.org/abs/2306.10376
In this paper, we propose a SOCratic model for Robots Approaching humans based on TExt System (SOCRATES) focusing on the human search and approach based on free-form textual description; the robot first searches for the target user, then the robot pr
Externí odkaz:
http://arxiv.org/abs/2302.05324
In this work, we present MoLang (a Motion-Language connecting model) for learning joint representation of human motion and language, leveraging both unpaired and paired datasets of motion and language modalities. To this end, we propose a motion-lang
Externí odkaz:
http://arxiv.org/abs/2210.15187
In this paper, we focus on the problem of efficiently locating a target object described with free-form language using a mobile robot equipped with vision sensors (e.g., an RGBD camera). Conventional active visual search predefines a set of objects t
Externí odkaz:
http://arxiv.org/abs/2209.08803
Text-based motion generation models are drawing a surge of interest for their potential for automating the motion-making process in the game, animation, or robot industries. In this paper, we propose a diffusion-based motion synthesis and editing mod
Externí odkaz:
http://arxiv.org/abs/2209.00349