TL;DR本论文提出了一种基于深度相机和惯性传感器的微型机器人系统的新型密集 SLAM 的框架,使用非迭代的 Fourier 变换来减少计算需求,通过解耦 6 自由度数据和进行独立空间点云匹配,实现分类键帧训练以及数据关联,相较现有方法,其速度更快,分辨率更高,但精度相当。
Abstract
The goal of this paper is to create a new framework for dense slam that is
light enough for micro-robot systems based on depth camera and inertial sensor.
Feature-based and direct methods are two mainstreams in v