works on

From the 1 of 5 linked papers with an AI index.

most citedAttention-Based Neural-Augmented Kalman Filter for Legged Robot State Estimation

2 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

cs.RO2026

ADP: Adversarial Dynamics Priors for Physically Grounded Humanoid Locomotion

Seokju Lee, Jeongtae Lee, Jeonghyeok Lim +6

The paper introduces Adversarial Dynamics Priors (ADP), a method that uses adversarial training on dynamics features such as center‑of‑mass motion and contact forces to make humano…

cs.RO20262 cited

Attention-Based Neural-Augmented Kalman Filter for Legged Robot State Estimation

Seokju Lee, Kyung-Soo Kim

In this letter, we propose an Attention-Based Neural-Augmented Kalman Filter (AttenNKF) for state estimation in legged robots. Foot slip is a major source of estimation error: when…

cs.RO2026

RAY-TOLD: Ray-Based Latent Dynamics for Dense Dynamic Obstacle Avoidance with TDMPC

Seungho Han, Seokju Lee, Jeonguk Kang

Dense, dynamic crowds pose a persistent challenge for autonomous mobile robots. Purely reactive planning methods, such as Model Predictive Path Integral (MPPI) control, often fail…

cs.RO2026

Legged Robot State Estimation Using Invariant Neural-Augmented Kalman Filter with a Neural Compensator

Seokju Lee, Hyun-Bin Kim, Kyung-Soo Kim

This paper presents an algorithm to improve state estimation for legged robots. Among existing model-based state estimation methods for legged robots, the contact-aided invariant e…

eess.SP2025

Temperature Compensation Method of Six-Axis Force/Torque Sensor Using Gated Recurrent Unit

Hyun-Bin Kim, Seokju Lee, Byeong-Il Ham +1

This study aims to enhance the accuracy of a six-axis force/torque sensor compared to existing approaches that utilize Multi-Layer Perceptron (MLP) and the Least Square Method. The…