The effect of sampling methods on Deep Q-Networks in robot navigation tasks

Enabling mobile robots to autonomously navigate complex environments is essential for real-world deployment in commercial, industrial, military, health care, and domestic settings. Prior methods approach this problem by having the robot maintain an internal map of the world and then use a localization and planning method to navigate through the...

Multimodal Deep Learning for the Classification of Human Activity: Radar and Video data fusion for the classification of human activity

Persistent surveillance is an urgent proficiency. For security, surveillance cameras are a strong asset as they support the automatic tracking of people and are directly interpretable by a human operator. Radar on the other hand can be used under a broad range of circumstances: radar can penetrate mediums such as clouds, fogs, mist and snow, and...