Výsledky vyhledávání - "Kim, HyeongJun"

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Legged Robot State Estimation With Invariant Extended Kalman Filter Using Neural Measurement Network

Autor: Youm, Donghoon, Oh, Hyunsik, Choi, Suyoung, Kim, Hyeongjun, Hwangbo, Jemin

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

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Imitating and Finetuning Model Predictive Control for Robust and Symmetric Quadrupedal Locomotion

Autor: Youm, Donghoon, Jung, Hyunyoung, Kim, Hyeongjun, Hwangbo, Jemin, Park, Hae-Won, Ha, Sehoon

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

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Akademický článek

Water‐Soluble, Spin‐Cast‐Based Crystalline Poly(Methacrylic Acid) Film as a Reversible Li‐Ion Battery Anode.

Autor: Son, Minjin¹ (AUTHOR), Kim, Hyeongjun¹ (AUTHOR), Lee, Minju¹ (AUTHOR), Na, Jonggeon¹ (AUTHOR), Kwak, Sang Kyu² (AUTHOR) skkwak@korea.ac.kr, Kang, Seok Ju¹ (AUTHOR) sjkang@unist.ac.kr

Publikováno v: Small Structures. Sep2024, p1. 10p. 6 Illustrations.

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Concurrent Training of a Control Policy and a State Estimator for Dynamic and Robust Legged Locomotion

Autor: Ji, Gwanghyeon, Mun, Juhyeok, Kim, Hyeongjun, Hwangbo, Jemin

Publikováno v: IEEE Robotics and Automation Letters (Volume: 7, Issue: 2, April 2022)

In this paper, we propose a locomotion training framework where a control policy and a state estimator are trained concurrently. The framework consists of a policy network which outputs the desired joint positions and a state estimation network which

Externí odkaz: http://arxiv.org/abs/2202.05481

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