In robotics, I take the approach to combine theory with practice, I first test my algorithms in simulations that I can easily design and modify and then I deploy my ideas to real robotic applications. I have built many robots including wheeled-cars, hexapods and robotic arms. Different types of robots are used in different scenarios in my project to simulate real life use cases. For example, when I was testing out the self-organizing behaviours on wheel-ed robots to find out maximum coverage of an area, I was also thinking about how this self-organizing behaviour could make vacuum cleaning robots more efficient in route planning. I have been following some of recent research projects such as TRADR, a disaster rescue robot. This robot would be more efficient with our algorithm if it can explore its environment in a systematic way and generate more exploratory behaviours.
The foundations for this neurorobotics are machine learning, control theory and brain theory. I like the fact that many ML theories are firstly proposed by inspiration of other fields and then tested, proved and challenged. The abstraction from the big data is so fascinating to me, they show us a logical world where your observation of it is shaped by your own perception. This is clear for robots; can you honestly say it’s entirely different for humans?
Computer Vision and NLP are also important in robotics. In the final-year system design project, I am responsible for the vision part of our group’s blackboard cleaning robot. I use bounding boxes to cluster the cleaning area for the robot to efficiently plan the desired cleaning pattern. I have also done software development projects with robot simulation using Unity ml-agents lib and Core ML in Swift.
I like participating in many hackathons, e.g. 2018 Oxford Hack, 2019 Hack the Burgh V and 2019 Great Uni Hack. In these hackathons, I built up teams and we worked on interesting industrial problems, e.g. the digital queueing system, speech-to-text recognition system. When we worked on an idea and after 24 hours we got excellent results, I felt motivated to acquire more and practice more.