23 citations · 40 across the 13 of their papers we have counts for
13 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…
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…
DVN-SLAM: Dynamic Visual Neural SLAM Based on Local-Global Encoding
Wenhua Wu, Guangming Wang, Ting Deng +5
Recent research on Simultaneous Localization and Mapping (SLAM) based on implicit representation has shown promising results in indoor environments. However, there are still some c…
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…