Novel sensory-motor coupling in soft robotic systems

Lead Research Organisation: University of Bristol
Department Name: Mechanical Engineering


The use of soft, flexible technologies in robotic systems is a fundamental shift from the traditional basis of how a robot should be designed. Compliant, deformable materials allow many biological principles to be emulated and this emerging soft approach can create robots that robustly deal with uncertainty, interact more safely with humans and compliantly move through unstructured environments.
The inherent compliance in soft robotic systems can be exploited to devolve computation away from the central high-level processor. This approach takes inspiration from nature, where organisms such as octopuses reduce computational demands on their brain by embodying intelligence into their tentacles. Biological species achieve such advanced behaviour through carefully tuned morphological parameters and a high integration of muscle and sensory elements.
This PhD will investigate how a soft robotic system's artificial muscles can be integrated with local sensory receptors to enable low-level computation through proprioceptive and environmental interaction. Inspired by nature, where sensory neurons often synapse in the spinal cord rather than the brain, novel technologies will be developed to enable dynamic low-level responses. This approach will be expanded by considering how different sensory modes can be exploited to create synaptic pathways to actuation.
Devolving computation to distributed sensory-motor elements in soft robots will lead to advances in the dynamic responsiveness of multiple degree-of-freedom systems and concomitant reductions in the computational loading of the central processor. Decentralising the control of the artificial muscles in soft robots will also improve their robustness to uncertainty as emergent behaviours can arise from localised sensory-motor interactions. It is envisaged that this PhD will make contributions towards the next generation of soft robotic system that can generate dynamic, multi-functional behaviours in a safe and efficient manner.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/N509619/1 01/10/2016 30/09/2021
1942482 Studentship EP/N509619/1 16/10/2017 15/05/2021 Alix Partridge
EP/R51245X/1 01/10/2017 30/09/2021
1942482 Studentship EP/R51245X/1 16/10/2017 15/05/2021 Alix Partridge