2 citations · 3 across the 5 of their papers we have counts for
5 papers
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…
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…
Towards Autonomous Selective Harvesting: A Review of Robot Perception, Robot Design, Motion Planning and Control
Vishnu Rajendran S, Bappaditya Debnath, Sariah Mghames +4
This paper provides an overview of the current state-of-the-art in selective harvesting robots (SHRs) and their potential for addressing the challenges of global food production. S…
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…