Maggie Huili Yao
Learning-Based Algorithms for Robotic Exploration with Tactile Feedback
2024–2025
Electrical Engineering and Computer Science
- Robotics
Daniela L. Rus
In an era dominated by computing devices and AI systems, significant obstacles to the broader adoption of robots such as understanding changing and unknown environments. This research project aims to address these challenges by leveraging robotic end effectors and limbs with integrated sensing to explore and map out unfamiliar environments through tactile interaction. In the initial phase, the focus is on deciphering interactions with the environment. This will be done through experimenting with existing model architectures to further refine them to identify object shapes solely through tactile feedback through techniques such as pose estimation and planar pushing mechanics. In the subsequent stage, I will be focusing on devising an exploration strategy for the surrounding environment.
I am participating in the SuperUROP program because I am interested in exploring the intersection between machine learning and robotics. I am excited to be able to develop additional research skills as well as pursue a more independent project. I have previously taken subjects in the domain and performed machine learning research, and so I hope to leverage my knowledge towards real-world applications.