  Monte Carlo Localization is a widely used approach in the field of mobile
robotics. While this problem has been well studied in the 2D case, global
localization in 3D maps with six degrees of freedom has so far been too
computationally demanding. Hence, no mobile robot system has yet been presented
in literature that is able to solve it in real-time. The computationally most
intensive step is the evaluation of the sensor model, but it also offers high
parallelization potential. This work investigates the massive parallelization
of the evaluation of particles in truncated signed distance fields for
three-dimensional laser scanners on embedded GPUs. The implementation on the
GPU is 30 times as fast and more than 50 times more energy efficient compared
to a CPU implementation.
