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pro vyhledávání: '"Yu, Byeongho"'
Autor:
Nahrendra, I Made Aswin, Yu, Byeongho, Oh, Minho, Lee, Dongkyu, Lee, Seunghyun, Lee, Hyeonwoo, Lim, Hyungtae, Myung, Hyun
Quadrupedal robots hold promising potential for applications in navigating cluttered environments with resilience akin to their animal counterparts. However, their floating base configuration makes them vulnerable to real-world uncertainties, yieldin
Externí odkaz:
http://arxiv.org/abs/2409.19709
Autor:
Jang, Seoyeon, Oh, Minho, Yu, Byeongho, Nahrendra, I Made Aswin, Lee, Seungjae, Lim, Hyungtae, Myung, Hyun
Safe navigation with simultaneous localization and mapping (SLAM) for autonomous robots is crucial in challenging environments. To achieve this goal, detecting moving objects in the surroundings and building a static map are essential. However, exist
Externí odkaz:
http://arxiv.org/abs/2408.05453
Autor:
Oh, Minho, Shin, Gunhee, Jang, Seoyeon, Lee, Seungjae, Lee, Dongkyu, Song, Wonho, Yu, Byeongho, Lim, Hyungtae, Lee, Jaeyoung, Myung, Hyun
Recognizing traversable terrain from 3D point cloud data is critical, as it directly impacts the performance of autonomous navigation in off-road environments. However, existing segmentation algorithms often struggle with challenges related to change
Externí odkaz:
http://arxiv.org/abs/2406.18138
Quadrupedal robots have emerged as a cutting-edge platform for assisting humans, finding applications in tasks related to inspection and exploration in remote areas. Nevertheless, their floating base structure renders them susceptible to fall in clut
Externí odkaz:
http://arxiv.org/abs/2306.12712
Quadrupedal robots resemble the physical ability of legged animals to walk through unstructured terrains. However, designing a controller for quadrupedal robots poses a significant challenge due to their functional complexity and requires adaptation
Externí odkaz:
http://arxiv.org/abs/2301.10602
Autor:
Nahrendra, I Made Aswin, Tirtawardhana, Christian, Yu, Byeongho, Lee, Eungchang Mason, Myung, Hyun
Studies that broaden drone applications into complex tasks require a stable control framework. Recently, deep reinforcement learning (RL) algorithms have been exploited in many studies for robot control to accomplish complex tasks. Unfortunately, dee
Externí odkaz:
http://arxiv.org/abs/2207.03124
We propose a novel state estimator for legged robots, STEP, achieved through a novel preintegrated foot velocity factor. In the preintegrated foot velocity factor, the usual non-slip assumption is not adopted. Instead, the end effector velocity becom
Externí odkaz:
http://arxiv.org/abs/2202.05572
Autor:
Lim, Hyunjun, Yu, Byeongho, Kim, Yeeun, Byun, Joowoong, Kwon, Soonpyo, Park, Haewon, Myung, Hyun
In this paper, WALK-VIO, a novel visual-inertial odometry (VIO) with walking-motion-adaptive leg kinematic constraints that change with body motion for localization of quadruped robots, is proposed. Quadruped robots primarily use VIO because they req
Externí odkaz:
http://arxiv.org/abs/2111.15164
Akademický článek
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Publikováno v:
In Solar Energy 1 March 2019 180:133-145