Image Processing and Interpretation (IPI), imec research group at Ghent University, Department of Telecommunications and Information Processing (TELIN), Ghent University, Sint-Pietersnieuwstraat 41, 9000 Gent, Belgium.
Sensors (Basel). 2018 Dec 21;19(1):23. doi: 10.3390/s19010023.
In this paper, we present a complete loop detection and correction system developed for data originating from lidar scanners. Regarding detection, we propose a combination of a global point cloud matcher with a novel registration algorithm to determine loop candidates in a highly effective way. The registration method can deal with point clouds that are largely deviating in orientation while improving the efficiency over existing techniques. In addition, we accelerated the computation of the global point cloud matcher by a factor of 2⁻4, exploiting the GPU to its maximum. Experiments demonstrated that our combined approach more reliably detects loops in lidar data compared to other point cloud matchers as it leads to better precision⁻recall trade-offs: for nearly 100% recall, we gain up to 7% in precision. Finally, we present a novel loop correction algorithm that leads to an improvement by a factor of 2 on the average and median pose error, while at the same time only requires a handful of seconds to complete.
本文提出了一个完整的环路检测和校正系统，专为激光雷达扫描仪产生的数据而开发。在检测方面，我们提出了一种全局点云匹配器与一种新颖的配准算法的组合，以高效地确定环路候选点。该配准方法可以处理在方向上有较大偏差的点云，同时提高了现有技术的效率。此外，我们通过利用 GPU 将全局点云匹配器的计算速度提高了 2⁻4 倍。实验表明，与其他点云匹配器相比，我们的组合方法更可靠地检测到激光雷达数据中的环路，因为它可以实现更好的精度⁻召回权衡：在接近 100%召回率的情况下，我们的精度提高了 7%。最后，我们提出了一种新的环路校正算法，平均和中位数姿态误差提高了 2 倍，同时只需要几秒钟即可完成。
