Aerial-Terrestrial-Aquatic Robots for Search and Rescue in an ATA Extreme Environment

今年，我们完成了项目的主要部分，重点是ATA映射。为了估计空中-水上过渡过程中的点云，我们开发了一种新的多盒插值方法。我们基于我们提出的方法研究空中和水上点云的噪声特性。我们还开发了一种图像处理技术来预测我们是否应该融合点云。这允许机器人在过渡期间避免碰撞。我们使用热成像摄像机来绘制环境，通过开发一种基于机器学习的全景感知生成对抗网络来帮助机器人在黑暗的水下区域进行热成像到彩色图像的转换。

This year, we completed a major part of our project, focusing on ATA mapping. To estimate point clouds during aerial-aquatic transitions, we developed a new multi-box interpolation method. We based our proposed method on studying the noise characteristics of aerial and aquatic point clouds. We also developed an image processing technique to predict whether we should fuse point clouds or not. This allows the robot to avoid collisions during transitions. We mapped the environment using a thermal camera, which helps the robot to see in dark underwater areas by developed a machine learning-based panoptic perception-based generative adversarial network for thermal-to-color image translation.