Rendering the Directional TSDF for Tracking and Multi-Sensor Registration with Point-To-Plane Scale ICP

TL;DR

This paper introduces a rendering method for the Directional TSDF that enhances real-time tracking and mapping from RGB-D images, with improved accuracy, re-usability, and multi-sensor capabilities.

Contribution

It presents a rendering approach for the Directional TSDF, integrates color correction, and develops a combined ICP method with multi-sensor Sim3 refinement, advancing existing tracking techniques.

Findings

Improved tracking performance on established datasets.

Enhanced color-correctness at adjacent surfaces.

Effective multi-sensor pose refinement with Sim3 ICP.

Abstract

Dense real-time tracking and mapping from RGB-D images is an important tool for many robotic applications, such as navigation and manipulation. The recently presented Directional Truncated Signed Distance Function (DTSDF) is an augmentation of the regular TSDF that shows potential for more coherent maps and improved tracking performance. In this work, we present methods for rendering depth- and color images from the DTSDF, making it a true drop-in replacement for the regular TSDF in established trackers. We evaluate the algorithm on well-established datasets and observe that our method improves tracking performance and increases re-usability of mapped scenes. Furthermore, we add color integration which notably improves color-correctness at adjacent surfaces. Our novel formulation of combined ICP with frame-to-keyframe photometric error minimization further improves tracking results. Lastly, we introduce Sim3 point-to-plane ICP for refining pose priors in a multi-sensor scenario with different scale factors.