Graphs and ML for Robotics

We are joined by Abhishek Paudel, a PhD Student at George Mason University with a research focus on robotics, machine learning, and planning under uncertainty, using graph-based methods to enhance robot behavior. He explains how graph-based approaches can model environments, capture spatial relationships, and provide a framework for integrating multiple levels of planning and decision-making.

Guest

Abhishek Paudel: "Abhishek Paudel is a Computer Science PhD student at George Mason University. His research interests are in the areas of robotics, machine learning, and planning under uncertainty. His research focuses on improving the robot's abilities to adapt to multiple environments that the robot may or may not have seen before. He works towards developing techniques with sound theoretical foundations that enable a robot to introspect its behavior during deployment and, if necessary, switch to better behaviors that are learned beforehand or during deployment so as to improve the overall performance. "