A review on SLAM: Past, Present and Open Problems

Vortrag von Dr. Juan Nieto

Datum: 19.10.17  Zeit: 16.15 - 18.15  Raum: ETH HG G 19.2

Robot localization is a key capability needed to enable truly autonomous mobile robots. In this talk we will describe the SLAM (Simultaneous Localization and Mapping) problem, which consists in the concurrent construction of a model of the environment (the map), and the estimation of the state of the robot (localization) moving within it. We will first present the different and necessary components of a prototypical SLAM system, from the sensor data through the data association and loop closure to the state estimator. Then, we discuss some of the classical approaches to SLAM and show what is now the de-facto standard formulation. During the talk we will cover a broad set of topics including robustness and scalability in long-term mapping, metric and semantic representations for mapping. Furthermore, we will delineate open challenges and new research issues, that deserve careful scientific investigation.