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20242026
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cs.RO2025

3DSGrasp: 3D Shape-Completion for Robotic Grasp

Seyed S. Mohammadi, Nuno F. Duarte, Dimitris Dimou +8

Real-world robotic grasping can be done robustly if a complete 3D Point Cloud Data (PCD) of an object is available. However, in practice, PCDs are often incomplete when objects are…

cs.RO2025

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…

cs.RO2025

Learning to Evaluate Autonomous Behaviour in Human-Robot Interaction

Matteo Tiezzi, Tommaso Apicella, Carlos Cardenas-Perez +5

Evaluating and comparing the performance of autonomous Humanoid Robots is challenging, as success rate metrics are difficult to reproduce and fail to capture the complexity of robo…

cs.RO2025

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…

cs.RO2025

Reasoning in visual navigation of end-to-end trained agents: a dynamical systems approach

Steeven Janny, Hervé Poirier, Leonid Antsfeld +6

Progress in Embodied AI has made it possible for end-to-end-trained agents to navigate in photo-realistic environments with high-level reasoning and zero-shot or language-condition…

cs.RO2025

Mind the Error! Detection and Localization of Instruction Errors in Vision-and-Language Navigation

Francesco Taioli, Stefano Rosa, Alberto Castellini +5

Vision-and-Language Navigation in Continuous Environments (VLN-CE) is one of the most intuitive yet challenging embodied AI tasks. Agents are tasked to navigate towards a target go…