Tootfinder

Multi-Class Human/Object Detection on Robot Manipulators using Proprioceptive Sensing
Justin Hehli, Marco Heiniger, Maryam Rezayati, Hans Wernher van de Venn
https://arxiv.org/abs/2508.02425

Multi-Class Human/Object Detection on Robot Manipulators using Proprioceptive Sensing
In physical human-robot collaboration (pHRC) settings, humans and robots collaborate directly in shared environments. Robots must analyze interactions with objects to ensure safety and facilitate meaningful workflows. One critical aspect is human/object detection, where the contacted object is identified. Past research introduced binary machine learning classifiers to distinguish between soft and hard objects. This study improves upon those results by evaluating three-class human/object detecti…

Magneto-photoelectrochemical 2D heterojunction platform for biosensing detection
Tao Wang, Nan Zhang, Hongjie Huang, Yunhe An, Yunyun Dai, Yongrui Li, Nan Yang, Chaojie Yang, Xinran Zhou, Yucheng Zhu, Yingshan Ma, Lingling Huang, Yongtian Wang, Yang Liu, Zhiyong Yan
https://arxiv.org/abs/2507.11843…

Magneto-photoelectrochemical 2D heterojunction platform for biosensing detection
Photoelectrochemical (PEC) biosensors exhibit significant potential for biomolecule detection due to their high sensitivity and low background noise. However, their performance is severely constrained by the rapid recombination of photogenerated charge carriers. This study innovatively introduces a non-contact magnetic modulation strategy to suppress electron-hole recombination by manipulating carrier spin states, thereby significantly enhancing photoelectric conversion efficiency. Building on …