Search Results for author: Nicola Bellotto

Found 14 papers, 3 papers with code

Experimental Evaluation of ROS-Causal in Real-World Human-Robot Spatial Interaction Scenarios

no code implementations7 Jun 2024 Luca Castri, Gloria Beraldo, Sariah Mghames, Marc Hanheide, Nicola Bellotto

To bridge this gap, in our previous work we proposed ROS-Causal, a ROS-based framework designed for onboard data collection and causal discovery in human-robot spatial interactions.

Causal Discovery Causal Inference

Efficient Causal Discovery for Robotics Applications

no code implementations23 Oct 2023 Luca Castri, Sariah Mghames, Nicola Bellotto

Using robots for automating tasks in environments shared with humans, such as warehouses, shopping centres, or hospitals, requires these robots to comprehend the fundamental physical interactions among nearby agents and objects.

Causal Discovery

Qualitative Prediction of Multi-Agent Spatial Interactions

no code implementations30 Jun 2023 Sariah Mghames, Luca Castri, Marc Hanheide, Nicola Bellotto

The third approach implements a purely data-driven network for motion prediction, the output of which is post-processed to predict QTC spatial interactions.

motion prediction

A Neuro-Symbolic Approach for Enhanced Human Motion Prediction

1 code implementation23 Apr 2023 Sariah Mghames, Luca Castri, Marc Hanheide, Nicola Bellotto

Reasoning on the context of human beings is crucial for many real-world applications especially for those deploying autonomous systems (e. g. robots).

Human motion prediction motion prediction +2

Towards Long-term Autonomy: A Perspective from Robot Learning

no code implementations24 Dec 2022 Zhi Yan, Li Sun, Tomas Krajnik, Tom Duckett, Nicola Bellotto

In the future, service robots are expected to be able to operate autonomously for long periods of time without human intervention.

Causal Discovery of Dynamic Models for Predicting Human Spatial Interactions

no code implementations29 Oct 2022 Luca Castri, Sariah Mghames, Marc Hanheide, Nicola Bellotto

Exploiting robots for activities in human-shared environments, whether warehouses, shopping centres or hospitals, calls for such robots to understand the underlying physical interactions between nearby agents and objects.

Causal Discovery

Pedestrian Models for Autonomous Driving Part II: High-Level Models of Human Behavior

no code implementations26 Mar 2020 Fanta Camara, Nicola Bellotto, Serhan Cosar, Florian Weber, Dimitris Nathanael, Matthias Althoff, Jingyuan Wu, Johannes Ruenz, André Dietrich, Gustav Markkula, Anna Schieben, Fabio Tango, Natasha Merat, Charles W. Fox

Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles navigating through crowds on pedestrianized high-streets.

Autonomous Driving Descriptive

Pedestrian Models for Autonomous Driving Part I: Low-Level Models, from Sensing to Tracking

no code implementations26 Feb 2020 Fanta Camara, Nicola Bellotto, Serhan Cosar, Dimitris Nathanael, Matthias Althoff, Jingyuan Wu, Johannes Ruenz, André Dietrich, Charles W. Fox

Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles navigating through crowds on pedestrianized high-streets.

Autonomous Driving

Wavelet-based temporal models of human activity for anomaly detection in smart robot-assisted environments

no code implementations26 Feb 2020 Manuel Fernandez-Carmona, Sariah Mghames, Nicola Bellotto

This paper, therefore, presents a new approach for temporal modelling of long-term human activities with smart-home sensors, which is used to detect anomalous situations in a robot-assisted environment.

Anomaly Detection

Robot Perception of Static and Dynamic Objects with an Autonomous Floor Scrubber

1 code implementation24 Feb 2020 Zhi Yan, Simon Schreiberhuber, Georg Halmetschlager, Tom Duckett, Markus Vincze, Nicola Bellotto

The proposed system is based on multiple sensors including 3D and 2D lidar, two RGB-D cameras and a stereo camera.

Robotics

A Visual Neural Network for Robust Collision Perception in Vehicle Driving Scenarios

no code implementations3 Apr 2019 Qinbing Fu, Nicola Bellotto, Huatian Wang, F. Claire Rind, Hongxin Wang, Shigang Yue

This research addresses the challenging problem of visual collision detection in very complex and dynamic real physical scenes, specifically, the vehicle driving scenarios.

Autonomous Vehicles

A Directionally Selective Neural Network with Separated ON and OFF Pathways for Translational Motion Perception in a Visually Cluttered Environment

no code implementations23 Aug 2018 Qinbing Fu, Nicola Bellotto, Shigang Yue

With respect to biological findings underlying fly's physiology in the past decade, we present a directionally selective neural network, with a feed-forward structure and entirely low-level visual processing, so as to implement direction selective neurons in the fly's visual system, which are mainly sensitive to wide-field translational movements in four cardinal directions.

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