LAUSR

The emerging paradigm of Continuous-Time Simultaneous Localization And Mapping (CTSLAM) has become a competitive alternative to conventional discrete-time approaches in recent times and holds the additional promise of fusing multi-modal sensor setups in a truly generic manner, rendering its importance to robotic navigation and manipulation seminal. In this spirit, this work expands upon continuous-time concepts, evaluates their suitability in common stereo and stereo-inertial online configurations and provides an extensible, generic, robust and modular open-source implementation to the community. The presented experimental analysis records the performance of our approach in these setups against the state-of-the-art in discrete-time Simultaneous Localization And Mapping (SLAM) on established datasets, achieving competitive results, and provides a direct comparison between online discrete- and continuous-time approaches for the first time. Targeting the absence of open-sourced, continuous-time pipelines and their associated, oftentimes prohibitive, initial developmental overhead, our implementation is made public.