10 citations · 20 across the 8 of their papers we have counts for
8 papers
GAIT: Legged Robot Proprioceptive State Estimation with Attention over Inertial-Leg Tokens
Young-Rang Seo, Hajun Kim, Sangmin Kim +2
In this paper, we propose a method that applies Inertial-Leg (IL) tokenization to an attention-based network for proprioceptive state estimation in legged robots. Unlike existing l…
Dynamic Policy Learning for Legged Robot with Simplified Model Pretraining and Model-Homotopy-Inspired Transfer
Dongyun Kang, Min-Gyu Kim, Tae-Gyu Song +3
Generating dynamic motions for legged robots remains a challenging problem. While reinforcement learning has achieved notable success in various legged locomotion tasks, producing…
Dynamically-Consistent Trajectory Optimization for Legged Robots via Contact Point Decomposition
Sangmin Kim, Hajun Kim, Gijeong Kim +2
To generate reliable motion for legged robots through trajectory optimization, it is crucial to simultaneously compute the robot's path and contact sequence, as well as accurately…
A Modular Residual Learning Framework to Enhance Model-Based Approach for Robust Locomotion
Min-Gyu Kim, Dongyun Kang, Hajun Kim +1
This paper presents a novel approach that combines the advantages of both model-based and learning-based frameworks to achieve robust locomotion. The residual modules are integrate…
Design of a 3-DOF Hopping Robot with an Optimized Gearbox: An Intermediate Platform Toward Bipedal Robots
JongHun Choe, Gijeong Kim, Hajun Kim +3
This paper presents a 3-DOF hopping robot with a human-like lower-limb joint configuration and a flat foot, capable of performing dynamic and repetitive jumping motions. To achieve…
Learning Impact-Rich Rotational Maneuvers via Centroidal Velocity Rewards and Sim-to-Real Techniques: A One-Leg Hopper Flip Case Study
Dongyun Kang, Gijeong Kim, JongHun Choe +2
Dynamic rotational maneuvers, such as front flips, inherently involve large angular momentum generation and intense impact forces, presenting major challenges for reinforcement lea…
Multi-Sensor Fusion for Quadruped Robot State Estimation using Invariant Filtering and Smoothing
Ylenia Nisticò, Hajun Kim, João Carlos Virgolino Soares +3
This letter introduces two multi-sensor state estimation frameworks for quadruped robots, built on the Invariant Extended Kalman Filter (InEKF) and Invariant Smoother (IS). The pro…
Online Friction Coefficient Identification for Legged Robots on Slippery Terrain Using Smoothed Contact Gradients
Hajun Kim, Dongyun Kang, Min-Gyu Kim +2
This paper proposes an online friction coefficient identification framework for legged robots on slippery terrain. The approach formulates the optimization problem to minimize the…