Estimating a vehicles' own trajectory and generating precise maps of the environment are both important tasks for intelligent vehicles. Especially for the second task laser scanners are the sensor of choice as they provide precise range measurements. This work proposes an approach for simultaneous localization and mapping (SLAM) specifically designed for the Velodyne HDL-64E laser scanner which exhibits characteristics not present in most other systems. This comprises the continuous, spinning data acquisition and the relative high sensor noise. Together, these make standard SLAM approaches generate noisy maps and inaccurate trajectories. We show that it is possible to generate precise maps and localize therein in spite of not using wheel speed sensors or other information. The presented approach is evaluated on a novel, challenging 3D data set being made publicly available.