1 citations · 2 across the 11 of their papers we have counts for
12 papers
Estimating the Causal Impact of Social Navigation Signals in Corridor Scenarios
Francesco Baldo, Luca Castri, Gloria Beraldo +1
Deploying robots in human-shared environments requires deciding not only how to navigate, but also when dedicated social signals are worth emitting. Classic observation-based infer…
Causality-enhanced Decision-Making for Autonomous Mobile Robots in Dynamic Environments
Luca Castri, Gloria Beraldo, Nicola Bellotto
The growing integration of robots in shared environments-such as warehouses, shopping centres, and hospitals-demands a deep understanding of the underlying dynamics and human behav…
CAnDOIT: Causal Discovery with Observational and Interventional Data from Time-Series
Luca Castri, Sariah Mghames, Marc Hanheide +1
The study of cause-and-effect is of the utmost importance in many branches of science, but also for many practical applications of intelligent systems. In particular, identifying c…
neuROSym: Deployment and Evaluation of a ROS-based Neuro-Symbolic Model for Human Motion Prediction
Sariah Mghames, Luca Castri, Marc Hanheide +1
Autonomous mobile robots can rely on several human motion detection and prediction systems for safe and efficient navigation in human environments, but the underline model architec…
Experimental Evaluation of ROS-Causal in Real-World Human-Robot Spatial Interaction Scenarios
Luca Castri, Gloria Beraldo, Sariah Mghames +2
Deploying robots in human-shared environments requires a deep understanding of how nearby agents and objects interact. Employing causal inference to model cause-and-effect relation…
ROS-Causal: A ROS-based Causal Analysis Framework for Human-Robot Interaction Applications
Luca Castri, Gloria Beraldo, Sariah Mghames +2
Deploying robots in human-shared spaces requires understanding interactions among nearby agents and objects. Modelling cause-and-effect relations through causal inference aids in p…
Efficient Causal Discovery for Robotics Applications
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 physic…
Qualitative Prediction of Multi-Agent Spatial Interactions
Sariah Mghames, Luca Castri, Marc Hanheide +1
Deploying service robots in our daily life, whether in restaurants, warehouses or hospitals, calls for the need to reason on the interactions happening in dense and dynamic scenes.…
A Neuro-Symbolic Approach for Enhanced Human Motion Prediction
Sariah Mghames, Luca Castri, Marc Hanheide +1
Reasoning on the context of human beings is crucial for many real-world applications especially for those deploying autonomous systems (e.g. robots). In this paper, we present a ne…
Enhancing Causal Discovery from Robot Sensor Data in Dynamic Scenarios
Luca Castri, Sariah Mghames, Marc Hanheide +1
Identifying the main features and learning the causal relationships of a dynamic system from time-series of sensor data are key problems in many real-world robot applications. In t…
From Continual Learning to Causal Discovery in Robotics
Luca Castri, Sariah Mghames, Nicola Bellotto
Reconstructing accurate causal models of dynamic systems from time-series of sensor data is a key problem in many real-world scenarios. In this paper, we present an overview based…
Causal Discovery of Dynamic Models for Predicting Human Spatial Interactions
Luca Castri, Sariah Mghames, Marc Hanheide +1
Exploiting robots for activities in human-shared environments, whether warehouses, shopping centres or hospitals, calls for such robots to understand the underlying physical intera…