9 papers
A Comparative Study of Counterfactual Explainers for Graph Neural Networks Enabling Multiple Types of Graph Edit
Maria Myrto Villia, Filippos Gouidis, Theodore Patkos +1
Counterfactual explanations for graph-structured data seek to determine minimal and realistic modifications required in an input graph to alter a model's prediction to a predefined…
A Completion-Aware Framework for Impactful Counterfactual Explainability in Graph Neural Networks
Maria Myrto Villia, Filippos Gouidis, Theodore Patkos +1
In this study, we propose a novel pipeline for generic, model-agnostic, local-level counterfactual explainability in graph neural networks (GNNs). Although counterfactual explainer…
AgiPIX: Bridging Simulation and Reality in Indoor Aerial Inspection
Sasanka Kuruppu Arachchige, Juan Jose Garcia, Changda Tian +4
Autonomous indoor flight for critical asset inspection presents fundamental challenges in perception, planning, control, and learning. Despite rapid progress, there is still a lack…
INDOOR-LiDAR: Bridging Simulation and Reality for Robot-Centric 360 degree Indoor LiDAR Perception -- A Robot-Centric Hybrid Dataset
Haichuan Li, Changda Tian, Panos Trahanias +1
We present INDOOR-LIDAR, a comprehensive hybrid dataset of indoor 3D LiDAR point clouds designed to advance research in robot perception. Existing indoor LiDAR datasets often suffe…
A control scheme for collaborative object transportation between a human and a quadruped robot using the MIGHTY suction cup
Konstantinos Plotas, Emmanouil Papadakis, Drosakis Drosakis +2
In this work, a control scheme for human-robot collaborative object transportation is proposed, considering a quadruped robot equipped with the MIGHTY suction cup that serves both…
IndoorBEV: Joint Detection and Footprint Completion of Objects via Mask-based Prediction in Indoor Scenarios for Bird's-Eye View Perception
Haichuan Li, Changda Tian, Panos Trahanias +1
Detecting diverse objects within complex indoor 3D point clouds presents significant challenges for robotic perception, particularly with varied object shapes, clutter, and the co-…
Two-layer adaptive trajectory tracking controller for quadruped robots on slippery terrains
Despina-Ekaterini Argiropoulos, Dimitrios Papageorgiou, Michael Maravgakis +2
Task space trajectory tracking for quadruped robots plays a crucial role on achieving dexterous maneuvers in unstructured environments. To fulfill the control objective, the robot…
Probabilistic Contact State Estimation for Legged Robots using Inertial Information
Michael Maravgakis, Despina-Ekaterini Argiropoulos, Stylianos Piperakis +1
Legged robot navigation in unstructured and slippery terrains depends heavily on the ability to accurately identify the quality of contact between the robot's feet and the ground.…
Robust Contact State Estimation in Humanoid Walking Gaits
Stylianos Piperakis, Michael Maravgakis, Dimitrios Kanoulas +1
In this article, we propose a deep learning framework that provides a unified approach to the problem of leg contact detection in humanoid robot walking gaits. Our formulation acco…