Instructor: Prof. Volkan Isler
Final Project: Search for people with kinect using multi-robot reinforcement learning
Abstract:
Bayesian search is a technique to save thousands people every year in outdoor environment. However, searching for people in indoor environments is different. First, the robot has to build a map. Second, a robot has to localize itself. Third, people detection is not generally accurate. Fourth, to compute the best actions for the search is NP-hard problem due to the obstacles. Therefore, this research is about proposing an algorithm of search for people in an indoor environment using reinforcement learning. The experimental results demonstrate that this approach is able to reduce the uncertainty of search with reasonable computational performance.
Final project report [pdf]
PS: I got a full credit for the final project (30%).