6 papers
GRASPLAT: Enabling dexterous grasping through novel view synthesis
Matteo Bortolon, Nuno Ferreira Duarte, Plinio Moreno +3
Achieving dexterous robotic grasping with multi-fingered hands remains a significant challenge. While existing methods rely on complete 3D scans to predict grasp poses, these appro…
The Role of Touch: Towards Optimal Tactile Sensing Distribution in Anthropomorphic Hands for Dexterous In-Hand Manipulation
João Damião Almeida, Egidio Falotico, Cecilia Laschi +1
In-hand manipulation tasks, particularly in human-inspired robotic systems, must rely on distributed tactile sensing to achieve precise control across a wide variety of tasks. Howe…
Deep Learning in Mild Cognitive Impairment Diagnosis using Eye Movements and Image Content in Visual Memory Tasks
Tomás Silva Santos Rocha, Anastasiia Mikhailova, Moreno I. Coco +1
The global prevalence of dementia is projected to double by 2050, highlighting the urgent need for scalable diagnostic tools. This study utilizes digital cognitive tasks with eye-t…
Measuring Uncertainty in Shape Completion to Improve Grasp Quality
Nuno Ferreira Duarte, Seyed S. Mohammadi, Plinio Moreno +2
Shape completion networks have been used recently in real-world robotic experiments to complete the missing/hidden information in environments where objects are only observed in on…
HERB: Human-augmented Efficient Reinforcement learning for Bin-packing
Gojko Perovic, Nuno Ferreira Duarte, Atabak Dehban +3
Packing objects efficiently is a fundamental problem in logistics, warehouse automation, and robotics. When dealing with highly diverse 3D objects (household or grocery items), clo…
Ego-Foresight: Self-supervised Learning of Agent-Aware Representations for Improved RL
Manuel Serra Nunes, Atabak Dehban, Yiannis Demiris +1
Despite the significant advances in Deep Reinforcement Learning (RL) observed in the last decade, the amount of training experience necessary to learn effective policies remains on…