6 papers
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…
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…
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…
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.…
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…
Contact-Implicit Model Predictive Control: Controlling Diverse Quadruped Motions Without Pre-Planned Contact Modes or Trajectories
Gijeong Kim, Dongyun Kang, Joon-Ha Kim +2
This paper presents a contact-implicit model predictive control (MPC) framework for the real-time discovery of multi-contact motions, without predefined contact mode sequences or f…