Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Shim, Inwook"'
Autor:
Choe, Jun Hyeok, Shim, Inwook
UWB has recently gained new attention as an auxiliary sensor in the field of robot localization due to its compactness and ease of distance measurement. Consequently, various UWB-related localization and dataset research have increased. Despite this
Externí odkaz:
http://arxiv.org/abs/2407.03890
Publikováno v:
IEEE Robotics and Automation Letters, 8.8 (2023):4617-4624
Estimating the traversability of terrain should be reliable and accurate in diverse conditions for autonomous driving in off-road environments. However, learning-based approaches often yield unreliable results when confronted with unfamiliar contexts
Externí odkaz:
http://arxiv.org/abs/2305.18896
Traversability estimation for mobile robots in off-road environments requires more than conventional semantic segmentation used in constrained environments like on-road conditions. Recently, approaches to learning a traversability estimation from pas
Externí odkaz:
http://arxiv.org/abs/2211.11201
Publikováno v:
IEEE Robotics and Automation Letters, 8.2 (2023):888-895
For the safe and successful navigation of autonomous vehicles in unstructured environments, the traversability of terrain should vary based on the driving capabilities of the vehicles. Actual driving experience can be utilized in a self-supervised fa
Externí odkaz:
http://arxiv.org/abs/2209.06522
LiDAR is widely used to capture accurate 3D outdoor scene structures. However, LiDAR produces many undesirable noise points in snowy weather, which hamper analyzing meaningful 3D scene structures. Semantic segmentation with snow labels would be a str
Externí odkaz:
http://arxiv.org/abs/2208.04043
Integrating model-based machine learning methods into deep neural architectures allows one to leverage both the expressive power of deep neural nets and the ability of model-based methods to incorporate domain-specific knowledge. In particular, many
Externí odkaz:
http://arxiv.org/abs/2012.04926
Publikováno v:
In Pattern Recognition Letters October 2023 174:99-105
We introduce a novel method to automatically adjust camera exposure for image processing and computer vision applications on mobile robot platforms. Because most image processing algorithms rely heavily on low-level image features that are based main
Externí odkaz:
http://arxiv.org/abs/1708.07338
Autor:
Shim, Inwook, Shin, Seunghak, Bok, Yunsu, Joo, Kyungdon, Choi, Dong-Geol, Lee, Joon-Young, Park, Jaesik, Oh, Jun-Ho, Kweon, In So
This paper presents a vision system and a depth processing algorithm for DRC-HUBO+, the winner of the DRC finals 2015. Our system is designed to reliably capture 3D information of a scene and objects robust to challenging environment conditions. We a
Externí odkaz:
http://arxiv.org/abs/1509.06114
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