Patrick Emami

Mentor: Dr. Carl Crane, III
College of Engineering
"I got involved with research because I believe that society will greatly benefit from advances in the field of autonomous systems."


Computer Engineering



Research Interests

  • Autonomous Systems
  • Machine Learning
  • Pattern Recognition

Academic Awards

  • University Scholars Program
  • IEEE IROS Awards Paper Finalist


  • Center for Intelligent Machines and Robotics
  • Kappa Phi Epsilon


  • Emeritus at Gainesville

Hobbies and Interests

  • Playing Guitar
  • Reading
  • Coding
  • Movies

Research Description

Motion Planning for Autonomous Vehicles under Uncertain Conditions

This research project will involve adapting a control algorithm known as a Partially Observable Markov Decision Process (POMDP) to a motion planning problem for autonomous Unmanned Aerial Vehicles (UAVs). Given that the world is inherently stochastic and that there are limitations on the number and quality of sensors that a single UAV can have, it is often difficult for a UAV to obtain accurate measurements of its surroundings. In order to account for this uncertainty, POMDPs derive a control policy based on probabilistic methods. The purpose of developing such a control policy is to determine the course of action to take that has the highest probability of maximizing a certain reward. The space and time complexity of this algorithm is such that it is not able to be implemented on high-dimensional spaces. Therefore, my adaptation will be focused on addressing this limitation. For experimentation, navigation tasks will be simulated to test the effectiveness of the algorithm.