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Modular reconfigurable robotic systems

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  • Full or part time
    Dr Roderich Gross
  • Application Deadline
    Applications accepted all year round
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

Self-assembly processes are responsible for the generation of order in nature. They involve components at different scales, such as molecules, cells, organisms, and weather systems. Scientists across many disciplines believe that the study of physical models of self-assembly can help in understanding nature and in advancing technology.

This project addresses the design, implementation and study of a novel robot that is composed of centimetre-sized robotic units. The units could be self-propelled or externally propelled (e.g., see [3,4,5]). The units can self-assemble, in other words, physically bind with each other. They can disconnect at will. By self-assembly, they can autonomously organise into modular entities the properties of which can change on the fly (e.g., shape, strength, function). In the long run, this could lead to a new generation of adaptive hardware (transformable matter [2], devices, robots/vehicles, buildings etc). Tens to hundreds of these units are to be produced and their adaptation capabilities are to be demonstrated.

The project will be carried out in the Natural Robotics Lab [1].


Funding Notes

Prospective applicants should have a degree in a relevant subject (electrical engineering, mechatronics, etc) and possibly be experienced in the design of printed circuit boards.

Applicants can apply for a Scholarship from the University of Sheffield but should note that competition for these Scholarships is highly competitive. it will be possible to make Scholarship applications from the Autumn with a strict deadline in late January/early February. Specific information will appear:

How good is research at University of Sheffield in General Engineering?

FTE Category A staff submitted: 21.80

Research output data provided by the Research Excellence Framework (REF)

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