23 citations · 40 across the 13 of their papers we have counts for
11 papers · 1 filter
A Framework for Deploying Learning-based Quadruped Loco-Manipulation
Yadong Liu, Jianwei Liu, He Liang +1
Quadruped mobile manipulators offer strong potential for agile loco-manipulation but remain difficult to control and transfer reliably from simulation to reality. Reinforcement lea…
E-SDS: Environment-aware See it, Do it, Sorted - Automated Environment-Aware Reinforcement Learning for Humanoid Locomotion
Enis Yalcin, Joshua O'Hara, Maria Stamatopoulou +2
Vision-language models (VLMs) show promise in automating reward design in humanoid locomotion, which could eliminate the need for tedious manual engineering. However, current VLM-b…
Immersive Teleoperation Framework for Locomanipulation Tasks
Takuya Boehringer, Jonathan Embley-Riches, Karim Hammoud +2
Recent advancements in robotic loco-manipulation have leveraged Virtual Reality (VR) to enhance the precision and immersiveness of teleoperation systems, significantly outperformin…
Unreal Robotics Lab: A High-Fidelity Robotics Simulator with Advanced Physics and Rendering
Jonathan Embley-Riches, Jianwei Liu, Simon Julier +1
High-fidelity simulation is essential for robotics research, enabling safe and efficient testing of perception, control, and navigation algorithms. However, achieving both photorea…
Exploring Adversarial Obstacle Attacks in Search-based Path Planning for Autonomous Mobile Robots
Adrian Szvoren, Jianwei Liu, Dimitrios Kanoulas +1
Path planning algorithms, such as the search-based A*, are a critical component of autonomous mobile robotics, enabling robots to navigate from a starting point to a destination ef…
Watch Your STEPP: Semantic Traversability Estimation using Pose Projected Features
Sebastian Ægidius, Dennis Hadjivelichkov, Jianhao Jiao +2
Understanding the traversability of terrain is essential for autonomous robot navigation, particularly in unstructured environments such as natural landscapes. Although traditional…
Real-Time Metric-Semantic Mapping for Autonomous Navigation in Outdoor Environments
Jianhao Jiao, Ruoyu Geng, Yuanhang Li +7
The creation of a metric-semantic map, which encodes human-prior knowledge, represents a high-level abstraction of environments. However, constructing such a map poses challenges r…
SDS -- See it, Do it, Sorted: Quadruped Skill Synthesis from Single Video Demonstration
Maria Stamatopoulou, Jeffrey Li, Dimitrios Kanoulas
Imagine a robot learning locomotion skills from any single video, without labels or reward engineering. We introduce SDS ("See it. Do it. Sorted."), an automated pipeline for skill…
DiPPeST: Diffusion-based Path Planner for Synthesizing Trajectories Applied on Quadruped Robots
Maria Stamatopoulou, Jianwei Liu, Dimitrios Kanoulas
We present DiPPeST, a novel image and goal conditioned diffusion-based trajectory generator for quadrupedal robot path planning. DiPPeST is a zero-shot adaptation of our previously…
On the Benefits of GPU Sample-Based Stochastic Predictive Controllers for Legged Locomotion
Giulio Turrisi, Valerio Modugno, Lorenzo Amatucci +2
Quadrupedal robots excel in mobility, navigating complex terrains with agility. However, their complex control systems present challenges that are still far from being fully addres…
DiPPeR: Diffusion-based 2D Path Planner applied on Legged Robots
Jianwei Liu, Maria Stamatopoulou, Dimitrios Kanoulas
In this work, we present DiPPeR, a novel and fast 2D path planning framework for quadrupedal locomotion, leveraging diffusion-driven techniques. Our contributions include a scalabl…