Follow the Soldiers with Optimized Single-Shot Multibox Detection and
  Reinforcement Learning
Jumman Hossain Maliha Momtaz
Nowadays, autonomous cars are gaining traction due to their numerous
potential applications on battlefields and in resolving a variety of other
real-world challenges. The main goal of our project is to build an autonomous
system using DeepRacer which will follow a specific person (for our project, a
soldier) when they will be moving in any direction. Two main components to
accomplish this project is an optimized Single-Shot Multibox Detection (SSD)
object detection model and a Reinforcement Learning (RL) model. We accomplished
the task using SSD Lite instead of SSD and at the end, compared the results
among SSD, SSD with Neural Computing Stick (NCS), and SSD Lite. Experimental
results show that SSD Lite gives better performance among these three
techniques and exhibits a considerable boost in inference speed (~2-3 times)
without compromising accuracy.