Publications associées à A data-efficient and general-purpose hand–eye calibration method for robotic systems using next best view

Publications associées (9)

Experimental assessment, design, and control of compliance in dexterous robotic hands

The ability to make compliant physical interactions enables robots to robustly contact with the environment. This plays a significant role in advancing robotic hands which must constantly interact with the world, often with large uncertainties and variatio ...

EPFL2025

A Bio-Inspired Learning and Control Framework for Cross-Embodiment and Cross-Task Locomotion

Milad Shafiee Ashtiani

Animals exhibit remarkable locomotion skills despite significant sensorimotor delays and operating in uncertain environments. Moreover, mammals acquire these skills within minutes of birth. From the Cambrian explosion to the present day, vertebrate motor c ...

EPFL2025

DiffCheck: A scan-CAD evaluation tool for digital manufacturing and assembly processes in timber construction

Yves Weinand, Julien Gamerro, Stefana Parascho, Andrea Settimi, Marianthi Eririni Kladeftira, Eleni Maria Skevaki, Damien Lambert Alain Félicien Gilliard

In digital timber construction, scanning technologies and point cloud data are widely used due to the accessibility of affordable 3D sensors, photogrammetry, and userfriendly CAD tools. While typically not employed for accuracy checks in timber fabrication ...

CRC Press2025

On the Perspectives of Image-to-Lidar Constraints in Dynamic Network Optimisation

Thibaut Stoltz, Jan Skaloud, Davide Antonio Cucci, Laurent Valentin Jospin, Kyriaki Mouzakidou

The evolution of airborne mapping witnesses the introduction of hybrid lidar-camera systems to enhance data collection, i.e. to obtain simultaneously high-density point-cloud and texture. Yet, the common adjustment of both optical data streams is a nontriv ...

International Society for Photogrammetry and Remote Sensing2025

Exploiting Representation Similarities in Self-Supervised Learning for Vision Tasks

Thomas Grégoire Stegmüller

Recent progress in computer vision has been driven by a simple yet transformative observation: the potential of 30-year-old neural networks can be unlocked by massively scaling their parameters and the amount of human-labeled training data. This breakthrou ...

EPFL2025

Enabling Faster Locomotion of Planetary Rovers With a Mechanically-Hybrid Suspension

David Rodriguez Martinez

The exploration of the lunar poles and the collection of samples from the martian surface are characterized by shorter time windows demanding increased autonomy and speeds. Autonomous mobile robots must intrinsically cope with a wider range of disturbances ...

2024

Rearranging Deformable Linear Objects for Implicit Goals with Self-Supervised Planning and Control

Luyin Hu

The robotic manipulation of deformable linear objects is a frontier problem with many potential applications in diverse industries. However, most existing research in this area focuses on shape control for a provided explicit goal and does not consider phy ...

2024

Model-Based Fusion of GNSS and Multiple-IMUs

Jan Skaloud, Aman Sharma

Autonomous navigation of drones in environments with intermittently poor GNSS reception remains a complex problem with small and lightweight sensors. Conventional kinematic frameworks, fusing inertial sensors with satellite positioning, often falter under ...

IEEE2024

Using Motion Cues to Supervise Single-Frame Body Pose and Shape Estimation in Low Data Regimes

Pascal Fua, Mathieu Salzmann, Andrey Davydov

When enough annotated training data is available, supervised deep-learning. algorithms excel at estimating human body pose and shape using a single camera. The effects of too little such data being available can be mitigated by using other information sour ...

Journal of Machine Learning Research Inc.2024