Low-viewpoint forest depth dataset for sparse rover swarms

TL;DR

This paper introduces a new dataset of over 9,700 synchronized RGB images and depth maps captured from a forest environment, aimed at advancing monocular depth prediction for autonomous forest navigation by small robot swarms.

Contribution

The authors present a large, diverse dataset of forest scenes with synchronized image and depth data, along with hardware and methodology details for data collection, to support research in robot navigation.

Findings

Dataset includes 9,700 image-depth pairs with varied conditions.

Provides detailed hardware setup and data collection methodology.

Aims to facilitate progress in monocular depth estimation for forest robots.

Abstract

Rapid progress in embedded computing hardware increasingly enables on-board image processing on small robots. This development opens the path to replacing costly sensors with sophisticated computer vision techniques. A case in point is the prediction of scene depth information from a monocular camera for autonomous navigation. Motivated by the aim to develop a robot swarm suitable for sensing, monitoring, and search applications in forests, we have collected a set of RGB images and corresponding depth maps. Over 100k images were recorded with a custom rig from the perspective of a small ground rover moving through a forest. Taken under different weather and lighting conditions, the images include scenes with grass, bushes, standing and fallen trees, tree branches, leafs, and dirt. In addition GPS, IMU, and wheel encoder data was recorded. From the calibrated, synchronized, aligned and timestamped frames about 9700 image-depth map pairs were selected for sharpness and variety. We provide this dataset to the community to fill a need identified in our own research and hope it will accelerate progress in robots navigating the challenging forest environment. This paper describes our custom hardware and methodology to collect the data, subsequent processing and quality of the data, and how to access it.