arXiv AI

Idiobionics: The Unification of Privacy and Intelligent Robotic Prostheses

arXiv:2607. 07775v1 Announce Type: new Abstract: The human body is at the center of a growing family of technologies designed to tightly and persistently couple biological and digital systems.

arXiv AI
Jul 8

Responsible Personalisation: The Double-Edged Sword of Personalisation in Human-Robot Interaction

arXiv:2607. 06344v1 Announce Type: cross Abstract: While personalisation is becoming a defining capability in human-robot interaction (HRI), the existing literature on responsible personalisation remains fragmented, offering isolated accounts of ethical risks without a structured understanding of how they emerge across interaction contexts.

By Antonio Andriella, Jauwairia Nasir, Andrea Rezzani, Alyssa Kubota, Dimitri Lacroix, Tamlin Love, Aniol Civit, Vicky Charisi, Elisabeth Andre, Wing-Yue Geoffrey Louie
Hugging Face Trending Papers
Jul 7

Responsible Personalisation: The Double-Edged Sword of Personalisation in Human-Robot Interaction

While personalisation is becoming a defining capability in human-robot interaction (HRI), the existing literature on responsible personalisation remains fragmented, offering isolated accounts of ethical risks without a structured understanding of how they emerge across interaction contexts. This gap is particularly critical in HRI, where robots' embodiment and social presence can amplify and reshape such risks or generate new types of risks.

arXiv Machine Learning
1d ago

MiDAS: A Multimodal Data Acquisition System and Dataset for Robot-Assisted Minimally Invasive Surgery

arXiv:2602. 12407v3 Announce Type: replace-cross Abstract: Background: Robot-assisted minimally invasive surgery (RMIS) research increasingly relies on multimodal data, yet access to proprietary robot telemetry remains a major barrier.

By Keshara Weerasinghe (MD), Seyed Hamid Reza Roodabeh (MD), Andrew Hawkins (MD), Zhaomeng Zhang, Zachary Schrader, Homa Alemzadeh
arXiv AI
Jul 20

EgoExoMoCap: Distributed Ego-Exo Human Motion Capture

arXiv:2607. 15868v1 Announce Type: cross Abstract: Human motion capture from head-mounted devices (HMDs) offers a scalable way to acquire real-world human motion and interaction data, which is crucial for applications in embodied AI and VR/AR.

By Jiaxi Jiang, Bharat Lal Bhatnagar, Nan Yang, Lingni Ma, Sebastian Starke, Robin Kips, Nadine Bertsch, Christian Holz, Federica Bogo
arXiv Machine Learning
Jul 14

Towards Real-World Wearable Motion Reconstruction

arXiv:2607. 09780v1 Announce Type: cross Abstract: The modern-day surge in popularity of wearable devices poses a fundamentally unique motion capture problem: reconstructing full-body movement from any set of sensing hardware worn at a given moment.

By Andrea Boscolo Camiletto, Rishabh Dabral, Eduardo Alvarado, Thabo Beeler, Marc Habermann, Christian Theobalt