ActiveGAMER: Active GAussian Mapping through Efficient Rendering

TL;DR

ActiveGAMER is an efficient active mapping system that uses 3D Gaussian Splatting for real-time scene reconstruction, outperforming traditional methods in accuracy and exploration efficiency.

Contribution

It introduces a novel active mapping framework leveraging 3D Gaussian Splatting with a rendering-based information gain module for improved exploration and reconstruction.

Findings

Achieves state-of-the-art geometric and photometric accuracy.

Outperforms existing methods on benchmark datasets.

Enables efficient real-time exploration in complex environments.

Abstract

We introduce ActiveGAMER, an active mapping system that utilizes 3D Gaussian Splatting (3DGS) to achieve high-quality, real-time scene mapping and exploration. Unlike traditional NeRF-based methods, which are computationally demanding and restrict active mapping performance, our approach leverages the efficient rendering capabilities of 3DGS, allowing effective and efficient exploration in complex environments. The core of our system is a rendering-based information gain module that dynamically identifies the most informative viewpoints for next-best-view planning, enhancing both geometric and photometric reconstruction accuracy. ActiveGAMER also integrates a carefully balanced framework, combining coarse-to-fine exploration, post-refinement, and a global-local keyframe selection strategy to maximize reconstruction completeness and fidelity. Our system autonomously explores and reconstructs environments with state-of-the-art geometric and photometric accuracy and completeness, significantly surpassing existing approaches in both aspects. Extensive evaluations on benchmark datasets such as Replica and MP3D highlight ActiveGAMER's effectiveness in active mapping tasks.