Factor Graphs for Robot Perception

1305 Newell Simon Hall

Abstract: Factor graphs have become a popular tool for modeling robot perception problems. Not only can they model the bipartite relationship between sensor measurements and variables of interest for inference, but they have also been instrumental in devising novel inference algorithms that exploit the spatial and temporal structure inherent in these problems. I will overview [...]

Scaling up Self-Supervision for Robot Learning

GHC 8102

Abstract: A general purpose robot will need to interact with objects in cluttered environments with minimal supervision. Machine learning provides methods that can deal with these complex tasks without explicitly modelling the environment. More recently, deep learning techniques combined with large scale data has revolutionized the fields of computer vision, language processing and reinforcement learning. [...]