Human ergonomics during human-robot collaboration
Dr S Chakrabarty
Dr M Dogar
No more applications being accepted
Competition Funded PhD Project (European/UK Students Only)
As robots enter the manufacturing workforce, we see the need for applications where humans and robots collaborate. Examples include, but are not limited to, a human-robot team carrying a large heavy object, a robot fixing an object for a human to apply operations on it (e.g. drilling, cutting, polishing), or a robot handing over an object (e.g. a tool) to a human worker.
In all such cases, a robot must make certain choices about where to position the object, how to move the object, how much force to apply on the object, where to grasp on the object etc. All these choices have serious implications on human ergonomics during their collaboration. For a robot to make these choices that are comfortable and safe for the human, it must be able to predict and reason what is comfortable and safe from the human perspective for that given task.
Employing surface recordings of muscles during set restricted tasks and during collaborative tasks between robots and humans, we will identify the neurobiomechanical principles that define human activity, along with correlated measures of comfort and ease. This will be combined with kinematics and physical models to understand and develop a mathematical basis for these interactions.
In this PhD project, which will be a collaboration between School of Biomedical Sciences and School of Computing’s Robotics Lab, we will develop models for human ergonomics which can then be sensed and used by robots to create comfortable and safe interactions with humans. This will involve recording from people, designing experiments and using mathematical and engineering tools to analyse the data.
The Faculty of Biological Sciences is pleased to announce a number of fully-funded PhD studentships to start in Oct 2019, covering academic fees at UK/EU level and providing a stipend at research council rate (£15,009 for 2019-20) for 4 years. Candidates should have, or be expecting, a 2.1 or above at undergraduate level in a relevant subject. A range of projects, spanning the research areas of the faculty, are eligible for funding. Please apply online, clearly stating which project/supervisor you are interested in and including a CV and transcripts.
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