Pejman Iravani

Personal profile

Research interests

Profile

Pejman Iravani is a Senior Lecturer in Mechanical Engineering. His research is in the area of Robotics, Computer Vision and Machine Learning. His current work aims taking robots from factories into populated environments.

Research

Pejman's current research is looking into the technologies that will make robots operational in real-world environments such as homes, workplace, hospitals and so on. His vision is that within the next 10-15 years robots will be doing most of the unpleasant jobs that currently humans are doing.

Pejman and his team are developing various technologies, including sensing materials for artificial skins, machine learning methods for robots to learn autonomously, and control methods to make robots safe when in close proximity to humans.

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Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2006 2022

2 Active
10 Finished

Smart servohydraulic robot actuation

Georgilas, I., Plummer, A. & Iravani, P.

1/10/18 → 31/03/22

Project: UK industry

Electrical Aspects of Rain Generation

Cleaver, D., Du Bois, J. & Iravani, P.

1/07/17 → 31/08/20

Project: Other

Additive Constructed Trastibial Intelligent ProstHetic

Iravani, P. & Plummer, A.

1/12/17 → 28/05/19

Project: Central government, health and local authorities

Prosthetics

Muscle

3D printers

Medical problems

Microprocessor chips

Future Unmanned Aerial Systems Traffic Management (UTM)

Cleaver, D., Du Bois, J. & Iravani, P.

1/05/17 → 1/06/18

Project: Central government, health and local authorities

GCRF - Autonomous and Disposable Biosensor for Water Quality

Iravani, P.

18/07/16 → 31/03/17

Project: Research council

Research Output 2004 2019

20 Article
15 Conference contribution
13 Paper
8 Chapter
3 More

A support vector clustering based approach for driving style classification

Feng, Y., Pickering, S., Chappell, E., Iravani, P. & Brace, C., 1 Jun 2019, (Accepted/In press) In : International Journal of Machine Learning and Computing. 9, 3, p. 344-350 7 p.

Research output: Contribution to journal › Article

Driving Style Modelling with Adaptive Neuro-Fuzzy Inference System and Real Driving Data

Feng, Y., Pickering, S., Chappell, E., Iravani, P. & Brace, C., 1 Jan 2019, Advances in Human Aspects of Transportation - Proceedings of the AHFE 2018 International Conference on Human Factors in Transportation, 2018. Springer Verlag, p. 481-490 10 p. (Advances in Intelligent Systems and Computing; vol. 786).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Open Access

File

Fuzzy inference

Railroad cars

Dynamometers

Chassis

Fuzzy logic