Scanning Bot: Efficient Scan Planning using Panoramic Cameras

TL;DR

This paper introduces an autonomous scan planning method for panoramic RGB-D cameras that creates efficient, collision-free tours ensuring high coverage, significantly reducing scanning time and effort for 3D scene reconstruction.

Contribution

It presents a novel fully autonomous scan planner that optimizes viewpoint selection and path planning for panoramic cameras, outperforming existing methods in speed and coverage.

Findings

Achieved 99% scan coverage in real-world tests.

Up to 3 times faster than state-of-the-art planners.

Validated in both synthetic and real environments.

Abstract

Panoramic RGB-D cameras are known for their ability to produce high quality 3D scene reconstructions. However, operating these cameras involves manually selecting viewpoints and physically transporting the camera, making the generation of a 3D model time consuming and tedious. Additionally, the process can be challenging for novice users due to spatial constraints, such as ensuring sufficient feature overlap between viewpoint frames. To address these challenges, we propose a fully autonomous scan planning that generates an efficient tour plan for environment scanning, ensuring collision-free navigation and adequate overlap between viewpoints within the plan. Extensive experiments conducted in both synthetic and real-world environments validate the performance of our planner against state-of-the-art view planners. In particular, our method achieved an average scan coverage of 99 percent in the real-world experiment, with our approach being up to 3 times faster than state-of-the-art planners in total scan time.