New Paper Accepted by ICRA2022

We are very excited to share that our paper “Design and experimental investigation of a vibro-impact self-propelled capsule robot with orientation control” has been accepted for presentation as a contributed paper by the 2022 International Conference on Robotics and Automation (ICRA2022). This work was done the PhD students, Jiajia Zhang and Jiyuan Tian, co-supervised by Dr Dibin Zhu (Exeter) and Dr Shyam Prasad (Royal Devon and Exeter NHS Foundation Trust). Please read the preprint version of this paper from

https://arxiv.org/abs/2202.11784

New Paper on Percussive Drilling using Machine Learning Techniques

We are delighted to share this new research article “Feature-based intelligent models for optimisation of percussive drilling” done by the PhD student, Kenneth Afebu, co-supervised with Dr Evangelos Papatheou, published at Neural Networks.

Highlights:
• Impact motions of bit-rock interaction during percussive drilling are studied.
• Feature-based classifiers are adopted in categorising these impact motions.
• Simulated and experimental impact motions data are merged to train network models.
• Feature extraction from raw data is essential for optimising networks’ performance.
• 42% and 67% of the networks yield accuracies greater than 91% and 77% respectively.

https://www.sciencedirect.com/science/article/pii/S0893608022000314

New Survey Article on Small Bowel Modelling and Capsule Endoscopy

We are happy to share this survey paper on Small Bowel Modelling and its Applications for Capsule Endoscopy published in Mechatronics (Volume 83, May 2022, 102748). Thanks for all the co-authors for your contributions: Jiyuan TianLuigi Manfredi, Benjamin S. Terry, Shyam Prasad, Imdadur RahmanWojciech Marlicz, and Anastasios Koulaouzidis.

Highlights:

  • This survey covers the studies on small-bowel motor activities.
  • It studies the modelling of the capsule endoscope in the small intestine.
  • The modelling works include analytical and finite element methods.
  • Experimental investigation of the small intestine is fully reviewed.
  • It is suitable for robotic engineers who are developing intestinal devices.

https://www.sciencedirect.com/science/article/pii/S0957415822000071

New Book Chapter

Very happy to share this new book which provides the state-of-the-art on medical robots for GI endoscopy with my team’s contribution on the capsule-intestine contact modelling.
Endorobotics
https://www.elsevier.com/books/endorobotics/manfredi/978-0-12-821750-4

Successful PhD Viva – Kenneth Afebu

I am very pleased to announce and congratulate Kenneth Omokhagbo Afebu for successfully defended his PhD thesis entitled “Intelligent models for optimisation of the vibro-impact drilling system”, subject to minor corrections. Kenneth was supervised by me along with Dr Evangelos Papatheou.

The external examiner was Professor Zi-Qiang Lang from the University of Sheffield with the internal examiner, Dr Junning Chen and the independent chair, Dr Prakash Kripakaran.

After his viva, Kenneth will continue his research in my group working on the intelligent models for early detection of bowel cancer as a Postdoctoral Research Fellow funded by EPSRC New Horizons (EP/V047868/1).

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Successful PhD Viva – Zhi Zhang

I am very pleased to announce and congratulate Zhi Zhang for successfully defended his PhD thesis entitled “Control of Coexisting Attractors in Nonsmooth Dynamical Systems”, subject to minor corrections. Zhi is the first PhD at the Applied Dynamics and Control Lab supervised by me along with Prof. Jan Sieber.

Zhi’s external examiner was Professor Ekaterina Pavlovskaia from the University of Aberdeen with the internal examiner, Dr Evangelos Papatheou and the independent chair, Dr Yulei Wu.

After his viva, Zhi will continue his work on dynamics and control of nonsmooth dynamical systems (from a micro-robot’s perspective) in my lab as a Postdoctoral Research Associate funded by EPSRC Mathematical Sciences.

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LEAF Bronze Award

Applied Dynamics and Control lab in Exeter (ADCE) has been awarded Bronze Award in recognition of the actions undertaken to improve sustainability practices as part of the Laboratory Efficiency Assessment Framework (LEAF) in 2021.