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Modular and dynamically reconfigurable space hardware systems are a high priority for research and development as they can significantly decrease development costs, facilitate multiple payloads, and enable indefinite lifetime extension for space missions. Dr. Mark Post has led work in the European Commission-funded projects InFuse for modular approaches to robotic sensor fusion, MOSAR for robot-reconfigurable modular satellites, and STARFAB for a robotic space warehouse that manages spacecraft modules. Building on these advances, a critical component for these systems to reach their potential is the capability to autonomously reconfigure modular robotic systems based on semantics included in mission requirements, software and hardware limitations, and potential faults and failures. This PhD project will focus on developing and demonstrating the “intelligence” that will enable future space robots and satellites to assemble and adapt themselves to changing mission requirements and environments. A variety of potential AI methodologies could be applied, such as logical reasoning with set theory, probabilistic inference, or deep learning networks. Existing laboratory ecosystems of robot modules and a robot arm can be applied to physically demonstrating how autonomous reconfigurable robots can solve problems and accomplish new tasks through semantic self-reconfiguration. This project has the potential to be involved with, and contribute to, current international space technology research projects that are helping shape the future of space use and exploration.
This position is based entirely at the University of York.
How to Apply:
Applicants should apply via the University’s online application system at https://www.york.ac.uk/study/postgraduate-research/apply/. Please read the application guidance first so that you understand the various steps in the application process.
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