As LiDAR sensors have become ubiquitous, the need for an efficient LiDAR data compression algorithm has increased. Modern LiDARs produce gigabytes of scan data per hour and are often used in applications with limited compute, bandwidth, and storage resources. We present a fast, lossless compression algorithm for LiDAR range and attribute scan sequences including multiple-return range, signal, reflectivity, and ambient infrared. Our algorithm -- dubbed "Jiffy" -- achieves substantial compression by exploiting spatiotemporal redundancy and sparsity. Speed is accomplished by maximizing use of single-instruction-multiple-data (SIMD) instructions. In autonomous driving, infrastructure monitoring, drone inspection, and handheld mapping benchmarks, the Jiffy algorithm consistently outcompresses competing lossless codecs while operating at speeds in excess of 65M points/sec on a single core. In a typical autonomous vehicle use case, single-threaded Jiffy achieves 6x compression of centimeter-precision range scans at 500+ scans per second. To ensure reproducibility and enable adoption, the software is freely available as an open source library.
翻译:由于LiDAR传感器已变得无处不在,对高效的LiDAR数据压缩算法的需求已经增加。现代LiDARs每小时生成千兆字节扫描数据,并经常用于有限的计算、带宽和存储资源的应用中。我们为LiDAR射程和属性扫描序列(包括多个返回范围、信号、反射率和环境红外线)提出了一个快速、无损压缩算法。我们的算法 -- -- 称为“Jiffy” -- -- 通过利用空间时空冗余和广度实现大量压缩。通过最大限度地使用单导多功能数据(SIMD)指令实现了速度。在自主驾驶、基础设施监测、无人机检查和手持绘图基准中,Jiffy算法始终压低无损代码,同时以超过65M点/秒的速度运行单一核心。在典型的自动机动车辆使用中,单读吉菲(Jiffy)通过在500+次扫描中进行6x压缩了厘米范围扫描。确保开放的图书馆可以自由使用软件源。