4 citations · 4 across the 3 of their papers we have counts for
5 papers · 1 filter
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…
EL-AGHF: Extended Lagrangian Affine Geometric Heat Flow
Sangmin Kim, Hae-Won Park
We propose a constrained Affine Geometric Heat Flow (AGHF) method that evolves so as to suppress the dynamics gaps associated with inadmissible control directions. AGHF provides a…
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…
A Learning Framework for Diverse Legged Robot Locomotion Using Barrier-Based Style Rewards
Gijeong Kim, Yong-Hoon Lee, Hae-Won Park
This work introduces a model-free reinforcement learning framework that enables various modes of motion (quadruped, tripod, or biped) and diverse tasks for legged robot locomotion.…