Recurrent Neural Networks for fast and robust vibration-based ground classification on mobile robots
Summary
Recurrent Neural Networks for fast and robust vibration-based ground classification on mobile robots is a scholarly article[1].
Key Facts
Recurrent Neural Networks for fast and robust vibration-based ground classification on mobile robots's instance of is recorded as scholarly article[2].
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Recurrent Neural Networks for fast and robust vibration-based ground classification on mobile robots. Retrieved May 24, 2026, from https://4ort.xyz/entity/recurrent-neural-networks-for-fast-and-robust-vibration-based-ground-classification-on-mobile-robots
MLA“Recurrent Neural Networks for fast and robust vibration-based ground classification on mobile robots.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/recurrent-neural-networks-for-fast-and-robust-vibration-based-ground-classification-on-mobile-robots.
BibTeX@misc{4ortxyz_recurrent-neural-networks-for-fast-and-robust-vibration-based-ground-classification-on-mobile-robots_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Recurrent Neural Networks for fast and robust vibration-based ground classification on mobile robots}}, year = {2026}, url = {https://4ort.xyz/entity/recurrent-neural-networks-for-fast-and-robust-vibration-based-ground-classification-on-mobile-robots}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Recurrent Neural Networks for fast and robust vibration-based ground classification on mobile robots — https://4ort.xyz/entity/recurrent-neural-networks-for-fast-and-robust-vibration-based-ground-classification-on-mobile-robots (retrieved 2026-05-24)
