— Scan matching, the problem of registering two laser scans in order to determine the relative positions from which the scans were obtained, is one of the most heavily relied-upon tools for mobile robots. Current algorithms, in a trade-off for computational performance, employ heuristics in order to quickly compute an answer. Of course, these heuristics are imperfect: existing methods can produce poor results, particularly when the prior is weak. The computational power available to modern robots warrants a re-examination of these quality vs. complexity trade-offs. In this paper, we advocate a probabilistically-motivated scan-matching algorithm that produces higher quality and more robust results at the cost of additional computation time. We describe several novel implementations of this approach that achieve real-time performance on modern hardware, including a multi-resolution approach for conventional CPUs, and a parallel approach for graphics processing units (GPUs). We also pro...
Edwin B. Olson