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Other literature type . 2025
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Other literature type . 2025
License: CC BY
Data sources: Datacite
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Other literature type . 2025
License: CC BY
Data sources: Datacite
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Reimagining the wheel: when mechanical engineering meets AI

Authors: Gillespie, Stuart; Araujo Alvarez, Alexandra; Wen, Hongkai;

Reimagining the wheel: when mechanical engineering meets AI

Abstract

Reimagining the wheel – mechanical engineering meets AICyclopic is a UK-based autonomous mobility startup. Their modular EV platform could have a huge impact on society: helping people get around towns and cities, assisting in warehouses, handling ‘last mile’ deliveries, or even exploring other planets. At its heart is a patented centreless wheel that offers enhanced manoeuvrability and stability.Cyclopic’s unique EV platform has four integrated drive units, each connected to an independently acting centreless wheel to provide drive, steering, suspension and braking. Each drive unit is autonomous, with allsoftware housed directly within the drive system. With integrated AI, the platform could be used as a logistics and delivery robot, an autonomous transportation pod, or even a multi-purpose unmanned aerial vehicle.Through BridgeAI, the Cyclopic team carried out a feasibility study for an autonomous mobile robot (AMR) for warehouses. This demonstrated that advanced AI can work with Cyclopic’s mechanical levelling systemto provide automated balancing. Existing AMRs operating in tight, busy spaces have issues with stability, versatility, manoeuvrability and speed, and struggle to cope with slopes and obstacles. Cyclopic’s advanced electric drive system offers much greater precision.The Cyclopic team has been working with BridgeAI Independent Scientific Advisor Professor Hongkai Wen, who has helped them network with potential partners in academia and industry – including leading researchers at the Universities of Surrey, Warwick and Oxford. Professor Wen is helping them to explore new applications for the technology, providing technical guidance in areas such as adapting existing autonomous mobility algorithms to Cyclopic’s system, and refining a digital twin that can test algorithms in a controlled virtual environment.

This case study is published under the InnovateUK BridgeAI - Bespoke AI and Data Science Advice for SMEs offer. The Alan Turing Institute Independent Scientific Advisors (ISAs) offer transformative support to SMEs across BridgeAI sectors, enabling them to harness AI for both practical and strategic benefits. This initiative is supported by Innovate UK BridgeAI. We thank Allan Rallings, CEO and Founder and Carol Rallings, COO Innovator at Cyclopic, as well as ProfessorHongkai Wen, Independent Scientific Advisor for BridgeAI based at The Alan Turing Institute, for their significant contributions to the development of this case study. Special thanks to Alexandra Araujo Alvarez, Senior Research Community Manager for BridgeAI, Dominica D'Arcangelo, Programme Manager, and Punita Maisuria, Project Coordinator, for their leadership and support. We also acknowledge Stuart Gillespie for his role as the technical writer for this and other case studies in the programme. Additional thanks go to Aida Mehonic, Principal Researcher for Research Applications, and Shakir Laher from The Alan Turing Institute for their valuable reviews and feedback. This work is led by Dr. Vera Matser, Head of Skills and Principal Investigator for BridgeAI at The Alan Turing Institute. For any comments, questions, or collaboration opportunities with BridgeAI, please email: bridgeAI@turing.ac.uk.

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Keywords

autonomous mobile robot, autonomous mobility algorithms, startup, ev platform

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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