Characterizing SLAM Benchmarks and Performance: Open Loop

Abstract: Systematic study of SLAM might benefit from a design of experiments type of benchmarking approach, as well as means to gauge best possible performance versus nominal performance. One way to better understand SLAM systems is if a good set of benchmarks could be established for quickly gauging general performance. Using decision trees dominant SLAM benchmark and SLAM performance factors can be easily determined. They can then inform algorithm development. On the best possible performance, we advocate for the use of slo-mo processing, which provides practically no per-frame time constraint on the SLAM solver. The slo-mo results should be upper bounds on SLAM performance compared to the same method run with real-time constraints.

Coming soon. ¹