ORB-SLAM-CNN: Lessons in Adding Semantic Map Construction t1o Feature-Based SLAM

摘要

Recent work has integrated semantics into the 3D scene models produced by visual SLAM systems. Though these systems operate close to real time, there is lacking a study of the ways to achieve realtime performance by trading off between semantic model accuracy and computational requirements. ORB-SLAM2 provides good scene accuracy and real-time processing while not requiring CPUs [1]. Following a 'single view' approach of overlaying a dense semantic map over the sparse SLAM scene model, we explore a method for automatically timing the parameters of the system such that it operates in real time while maximizing prediction accuracy and map density.