Zobrazeno 1 - 10
of 239
pro vyhledávání: '"Park, Jeongeun"'
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
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
One of the most fundamental questions in quantum information theory is PPT-entanglement of quantum states, which is an NP-hard problem in general. In this paper, however, we prove that all PPT $(\overline{\pi}_A\otimes \pi_B)$-invariant quantum state
Externí odkaz:
http://arxiv.org/abs/2301.03849
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
Publikováno v:
In Redox Biology September 2024 75
Publikováno v:
In Materials Today Communications August 2024 40
Robust learning methods aim to learn a clean target distribution from noisy and corrupted training data where a specific corruption pattern is often assumed a priori. Our proposed method can not only successfully learn the clean target distribution f
Externí odkaz:
http://arxiv.org/abs/2111.01632
Autor:
Park, Sangbeom, Chai, Yoonbyung, Park, Sunghyun, Park, Jeongeun, Lee, Kyungjae, Choi, Sungjoon
In this paper, we present a semi-autonomous teleoperation framework for a pick-and-place task using an RGB-D sensor. In particular, we assume that the target object is located in a cluttered environment where both prehensile grasping and non-prehensi
Externí odkaz:
http://arxiv.org/abs/2109.13081