6 papers
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…
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…
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'…
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…
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…
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…