RT-GuIDE: Real-Time Gaussian splatting for Information-Driven Exploration

Abstract

We propose a framework for active mapping and exploration that leverages Gaussian splatting for constructing dense maps. Further, we develop a GPU-accelerated motion planning algorithm that can exploit the Gaussian map for real-time navigation. The Gaussian map constructed onboard the robot is optimized for both photometric and geometric quality while enabling real-time situational awareness for autonomy. We show through simulation experiments that our method yields comparable Peak Signal-to-Noise Ratio (PSNR) and similar reconstruction error to state-of-the-art approaches, while being orders of magnitude faster to compute. In real-world experiments, our algorithm achieves better map quality (at least 0.8dB higher PSNR and more than 16% higher geometric reconstruction accuracy) than maps constructed by a state-of-the-art method, enabling semantic segmentation using off-the-shelf open-set models.

Onboard constructed map

Full Video

Offline reconstruction from experiments.

System Overview

The proposed framework contains two major components, the planning module and the mapping module. As can be seen in the figure, the Mapping module ([A]) takes in RGB, depth and pose measurements, and updates the map representation at every step and computes the utility of cuboidal regions. The utility of each region is then passed to the planning module which comprises the topological graph and motion primitive library ([B]). The trajectory planner in turn attempts to plan a path to goal that maximizes information gathering (queried from the mapper). The planned trajectory is executed by the robot to get a new set of observations.

BibTeX

@misc{tao2024rtguiderealtimegaussiansplatting,
      title={RT-GuIDE: Real-Time Gaussian splatting for Information-Driven Exploration}, 
      author={Yuezhan Tao and Dexter Ong and Varun Murali and Igor Spasojevic and Pratik Chaudhari and Vijay Kumar},
      year={2024},
      eprint={2409.18122},
      archivePrefix={arXiv},
      primaryClass={cs.RO},
      url={https://arxiv.org/abs/2409.18122}, 
}