2 citations · 2 across the 4 of their papers we have counts for
12 papers
Green for Go, Red for No: Visual Grounding via Semantic Segmentation for VLA Navigation Policies
Adrian Szvoren, Dimitrios Kanoulas, Nilufer Tuptuk
Vision-language-action (VLA) models enable robot navigation from natural language and visual goals, but remain susceptible to perceptual distractions and ambiguous scene interpreta…
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…
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…
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…
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…