1.5k citations · 4.2k across the 24 of their papers we have counts for
25 papers · 1 filter
PolyMorph: Learning Locomotion Policy for Cross-Embodiment Adaptation
Hyunsik Oh, Seunghun Jeon, Donghoon Youm +5
Reinforcement learning has enabled robust locomotion for legged robots, but learned policies are typically tied to a specific robot morphology and require additional engineering wh…
DELTA: Deformable Elevation-Based Local Terrain Attention Encoder for Sparse-Terrain Quadrupedal Locomotion
Sanghyun Park, Moonkyu Jung, Jemin Hwangbo
Stable quadrupedal locomotion on sparse terrain requires selecting state-relevant terrain evidence for precise foot placement. Model-based foothold planners provide precise foothol…
TRACE: Learned Proprioceptive Odometry for Legged Robots under Unreliable Contact Conditions
Taehyeon Kong, Woojin Kim, Jemin Hwangbo
In this paper, we present TRACE (Tokenized Robust Attention for Contact-Aware Estimation), an end-to-end learned proprioceptive odometry estimator for legged robots under unreliabl…
PAKE: Learning Whole-Body Loco-Manipulation with Partial Kinematic Embeddings
Zhengmao He, Moonkyu Jung, Hyeongjun Kim +4
Loco-manipulation has recently shown promising capabilities; however, achieving high-precision control, managing the high-dimensional action space induced by many degrees of freedo…
Learning Dynamic Pick-and-Place for a Legged Manipulator
Moonkyu Jung, Jiseong Lee, Zhengmao He +8
Legged manipulators extend robotic capabilities beyond static manipulation by integrating agile locomotion with versatile arm control. However, achieving precise manipulation while…
Learning Quadrupedal Locomotion for a Heavy Hydraulic Robot Using an Actuator Model
Minho Lee, Hyeonseok Kim, Jin Tak Kim +4
The simulation-to-reality (sim-to-real) transfer of large-scale hydraulic robots presents a significant challenge in robotics because of the inherent slow control response and comp…
High-speed control and navigation for quadrupedal robots on complex and discrete terrain
Hyeongjun Kim, Hyunsik Oh, Jeongsoo Park +5
High-speed legged navigation in discrete and geometrically complex environments is a challenging task because of the high-degree-of-freedom dynamics and long-horizon, nonconvex nat…
Reference Free Platform Adaptive Locomotion for Quadrupedal Robots using a Dynamics Conditioned Policy
David Rytz, Suyoung Choi, Wanming Yu +3
This article presents Platform Adaptive Locomotion (PAL), a unified control method for quadrupedal robots with different morphologies and dynamics. We leverage deep reinforcement l…
Learning Rapid Turning, Aerial Reorientation, and Balancing using Manipulator as a Tail
Insung Yang, Jemin Hwangbo
In this research, we investigated the innovative use of a manipulator as a tail in quadruped robots to augment their physical capabilities. Previous studies have primarily focused…
Learning Semantic Traversability with Egocentric Video and Automated Annotation Strategy
Yunho Kim, Jeong Hyun Lee, Choongin Lee +4
For reliable autonomous robot navigation in urban settings, the robot must have the ability to identify semantically traversable terrains in the image based on the semantic underst…
Legged Robot State Estimation With Invariant Extended Kalman Filter Using Neural Measurement Network
Donghoon Youm, Hyunsik Oh, Suyoung Choi +2
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 net…
Imitating and Finetuning Model Predictive Control for Robust and Symmetric Quadrupedal Locomotion
Donghoon Youm, Hyunyoung Jung, Hyeongjun Kim +3
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 nove…
Learning Vehicle Dynamics from Cropped Image Patches for Robot Navigation in Unpaved Outdoor Terrains
Jeong Hyun Lee, Jinhyeok Choi, Simo Ryu +3
In the realm of autonomous mobile robots, safe navigation through unpaved outdoor environments remains a challenging task. Due to the high-dimensional nature of sensor data, extrac…
Learning Whole-body Manipulation for Quadrupedal Robot
Seunghun Jeon, Moonkyu Jung, Suyoung Choi +2
We propose a learning-based system for enabling quadrupedal robots to manipulate large, heavy objects using their whole body. Our system is based on a hierarchical control strategy…
ArtiGrasp: Physically Plausible Synthesis of Bi-Manual Dexterous Grasping and Articulation
Hui Zhang, Sammy Christen, Zicong Fan +4
We present ArtiGrasp, a novel method to synthesize bi-manual hand-object interactions that include grasping and articulation. This task is challenging due to the diversity of the g…
Not Only Rewards But Also Constraints: Applications on Legged Robot Locomotion
Yunho Kim, Hyunsik Oh, Jeonghyun Lee +5
Several earlier studies have shown impressive control performance in complex robotic systems by designing the controller using a neural network and training it with model-free rein…
Monte Carlo Tree Search Gait Planner for Non-Gaited Legged System Control
Lorenzo Amatucci, Joon-Ha Kim, Jemin Hwangbo +1
In this work, a non-gaited framework for legged system locomotion is presented. The approach decouples the gait sequence optimization by considering the problem as a decision-makin…
Learning Forward Dynamics Model and Informed Trajectory Sampler for Safe Quadruped Navigation
Yunho Kim, Chanyoung Kim, Jemin Hwangbo
For autonomous quadruped robot navigation in various complex environments, a typical SOTA system is composed of four main modules -- mapper, global planner, local planner, and comm…
Concurrent Training of a Control Policy and a State Estimator for Dynamic and Robust Legged Locomotion
Gwanghyeon Ji, Juhyeok Mun, Hyeongjun Kim +1
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 ou…
Learning robust perceptive locomotion for quadrupedal robots in the wild
Takahiro Miki, Joonho Lee, Jemin Hwangbo +3
Legged robots that can operate autonomously in remote and hazardous environments will greatly increase opportunities for exploration into under-explored areas. Exteroceptive percep…
Learning Quadrupedal Locomotion over Challenging Terrain
Joonho Lee, Jemin Hwangbo, Lorenz Wellhausen +2
Some of the most challenging environments on our planet are accessible to quadrupedal animals but remain out of reach for autonomous machines. Legged locomotion can dramatically ex…
Learning agile and dynamic motor skills for legged robots
Jemin Hwangbo, Joonho Lee, Alexey Dosovitskiy +4
Legged robots pose one of the greatest challenges in robotics. Dynamic and agile maneuvers of animals cannot be imitated by existing methods that are crafted by humans. A compellin…
Robust Recovery Controller for a Quadrupedal Robot using Deep Reinforcement Learning
Joonho Lee, Jemin Hwangbo, Marco Hutter
The ability to recover from a fall is an essential feature for a legged robot to navigate in challenging environments robustly. Until today, there has been very little progress on…
Cable-Driven Actuation for Highly Dynamic Robotic Systems
Jemin Hwangbo, Vassilios Tsounis, Hendrik Kolvenbach +1
This paper presents design and experimental evaluations of an articulated robotic limb called Capler-Leg. The key element of Capler-Leg is its single-stage cable-pulley transmissio…