activity
20192026
most citedSocNav1: A Dataset to Benchmark and Learn Social Navigation Conventions

29 citations · 33 across the 7 of their papers we have counts for

collaborators

10 papers

cs.RO2026

Concept-Guided Exploration: Building Persistent, Actionable Scene Graphs

Noé Zapata, Gerardo Pérez, Alejandro Torrejón +2

The perception of 3D space by mobile robots is rapidly moving from flat metric grid representations to hybrid metric-semantic graphs built from human-interpretable concepts. While…

cs.RO2024

Guessing human intentions to avoid dangerous situations in caregiving robots

Noé Zapata, Gerardo Pérez, Lucas Bonilla +3

For robots to interact socially, they must interpret human intentions and anticipate their potential outcomes accurately. This is particularly important for social robots designed…

cs.RO2023

SocNavGym: A Reinforcement Learning Gym for Social Navigation

Aditya Kapoor, Sushant Swamy, Luis Manso +1

It is essential for autonomous robots to be socially compliant while navigating in human-populated environments. Machine Learning and, especially, Deep Reinforcement Learning have…

cs.CV2022★ 4 cited

Multi-person 3D pose estimation from unlabelled data

Daniel Rodriguez-Criado, Pilar Bachiller, George Vogiatzis +1

Its numerous applications make multi-human 3D pose estimation a remarkably impactful area of research. Nevertheless, assuming a multiple-view system composed of several regular RGB…

cs.RO2021

A Graph Neural Network to Model Disruption in Human-Aware Robot Navigation

Pilar Bachiller, Daniel Rodriguez-Criado, Ronit R. Jorvekar +3

Autonomous navigation is a key skill for assistive and service robots. To be successful, robots have to minimise the disruption caused to humans while moving. This implies predicti…

cs.RO2020

Generation of Human-aware Navigation Maps using Graph Neural Networks

Daniel Rodriguez-Criado, Pilar Bachiller, Luis J. Manso

Minimising the discomfort caused by robots when navigating in social situations is crucial for them to be accepted. The paper presents a machine learning-based framework that boots…

cs.RO2020

A Toolkit to Generate Social Navigation Datasets

Rishabh Baghel, Aditya Kapoor, Pilar Bachiller +3

Social navigation datasets are necessary to assess social navigation algorithms and train machine learning algorithms. Most of the currently available datasets target pedestrians'…

cs.RO2020

Multi-camera Torso Pose Estimation using Graph Neural Networks

Daniel Rodriguez-Criado, Pilar Bachiller, Pablo Bustos +2

Estimating the location and orientation of humans is an essential skill for service and assistive robots. To achieve a reliable estimation in a wide area such as an apartment, mult…

cs.RO2019

Graph Neural Networks for Human-aware Social Navigation

Luis J. Manso, Ronit R. Jorvekar, Diego R. Faria +2

Autonomous navigation is a key skill for assistive and service robots. To be successful, robots have to navigate avoiding going through the personal spaces of the people surroundin…

cs.RO2019★ 29 cited

SocNav1: A Dataset to Benchmark and Learn Social Navigation Conventions

Luis J. Manso, Pedro Nunez, Luis V. Calderita +2

Adapting to social conventions is an unavoidable requirement for the acceptance of assistive and social robots. While the scientific community broadly accepts that assistive robots…