Robotic matter
We welcome Utku Culha with a bachelor’s and master’s degrees from Bilkent University, Turkey from the Computer Engineering Department.
Date and time: Thursday 2 July 2020, 12pm – 1pm
Speaker: Utcu Culha
Abstract: We typically have a clear idea about the final design and functionality of a robot before we start building it. We apply this top-down design approach to a wide range of robotic systems and it allows our robots to be more optimized, autonomous, and programmable. However, if we want to design and actuate multiple robots in miniature scales or robots made of continuously deforming materials, this approach sometimes fails to meet our needs. In these cases, we adopt another design strategy inspired by nature that manages to create complex morphologies and adaptive functions out of the collective motion of many neighbouring, soft, smaller and simpler elements. In this talk, I will describe how we can use this bottom-up design approach to build and control soft robotic self-assemblies in multiple length scales. I will talk about how we can benefit from engineering tools, fundamental laws of physics, and emerging machine learning methods to explore the vast design and function search space of self-assembling soft robots. Our findings can enable novel robotic systems for medical solutions, control strategies for robot swarms, and a stronger connection with soft matter physics and material science.
Bio: Utku Culha has received his bachelor’s and master’s degrees from Bilkent University, Turkey from the Computer Engineering Department. He started his PhD on Mechanical Engineering in ETH-Zurich, Switzerland with Prof. Fumiya Iida and then moved to the University of Cambridge, UK to help establish the Bio-Inspired Robotics Laboratory. During his PhD, Utku has worked on deforming thermoplastic materials for adaptive robotic sensing, locomotion, and manipulation. After completing his PhD, Utku joined the Physical Intelligence Department at the Max-Planck Institute (MPI) for Intelligent Systems in Stuttgart, Germany, and has been working as a Humboldt Postdoctoral researcher with Prof. Metin Sitti since 2016. Utku is interested in creating self-assembling soft robots that can physically adapt to their environment by deforming their body morphologies. He is also working on using data-efficient machine-learning methods to explore novel robot functions, designs, and controllers.