Pose Estimation Lunar Robot
Dataset for camera pose estimation research using computer simulated images from rovers on the lunar surface
Overview
The goal: using simulation data to train neural networks to estimate the pose of a rover's camera with respect to a known target object
The mission context: A simulated lunar surface, with lunar landers and lunar rovers. To accomplish their ressource extraction mission, the rovers must dig, transport and deliver regolith to a processing plant. For each of these tasks, a central need is for rovers to accurately estimate the relative pose both between themselves and with the landers.
<img src="https://github.com/TeamL3/learned-pose-estimation/raw/main/misc/images/overview_low.png" alt="lunar surface overview" style="width:720px;"/>The dataset:
- tf.data dataset ready for training (RGBD images and ground truth pose labels)
- five different scenarios for relative pose estimation, some easier, some harder!
The code:
Utilities for manipulating the dataset and calculating training metrics + example jupyter notebooks for data exploration and model training + more details on the dataset are available on github