Title: Mapping and Navigation with an Autonomous Car

Authors: Pierre Lamon, Cyrill Stachniss, Rudolph Triebel, Patrick Pfaff, Christian Plagemann, Girogio Grisetti, Sascha Kolski, Wolfram Burgard, Roland Siegwart.
　

Speaker: Wolfram Burgard

Affiliation: Autonomous Intelligent Systems, University of Freiburg

Abstract:
n this paper, we present an approach towards mapping and safe navigation in real, large-scale, and non-static environments. Our approach is designed to allow cars to autonomously navigate on roads while avoiding obstacles and while simultaneously learning an accurate three-dimensional model of the environment. To achieve these goals, we apply probabilistic state estimation techniques, network-based pose optimization, and a sensor-based traversability analysis approach. In order to achieve fast map learning, our system compresses the sensor data using multi-level surface maps. The overall systems has been implemented on an instrumented Smart car equipped with different types of sensors. We will present several experimental results illustrating the robustness of our approach in real-world scenarios.