Sebastian Thrun

A guide to deep learning in healthcare

Probabilistic robotics

Planning and navigation algorithms exploit statistics gleaned from uncertain, imperfect real-world environments to guide robots toward their goals and around obstacles.

Probabilistic Algorithms and the Interactive Museum Tour-Guide Robot Minerva

This paper describes Minerva, an interactive tour-guide robot that was successfully deployed in a Smithsonian museum. Minerva’s software is pervasively probabilistic, relying on...

Coordination for Multi-Robot Exploration and Mapping

This paper addresses the problem of exploration and mapping of an unknown environment by multiple robots. The mapping algorithm is an on-line approach to likelihood maximization...

Using EM to Learn 3D Models of Indoor Environments with Mobile Robots

This paper describes an algorithm for generating compact 3D models of indoor environments with mobile robots. Our algorithm employs the expectation maximization algorithm to fit...