At a Glance


PeRL studies autonomous navigation and mapping for mobile robots in a priori unknown environments.

Dig Deeper

Naval Engineering Education Center (NEEC)

Unmanned Landing

Autonomous systems are playing an ever growing, and more crucial role in the Navy active fleet. As such, the U.S. Navy has a need to educate and hire a cross-disciplinary civilian workforce who are trained in the science and technology behind the next-generation of autonomous systems. This NEEC project will crucially help to fill that role by educating and training an undergraduate and graduate student cohort in the cross-disciplinary system issues in developing robust autonomy for unmanned vehicle systems.

NEEC Project Objective

The center of focus of this project will be a multi agent unmanned vehicle system testbed that will allow the students to learn, train, and perform experiments with real unmanned vehicle systems. Proposed science and technology areas that students will work on are:

Autonomous mapping and navigation
Cooperative control and search
Computer vision, Lidar and multi-sensor fusion for robust intelligence
Kalman filtering, particle filtering, and Bayesian estimation methods
Robust autonomy
System integration
Embedded system programming
Sensing and perception
Control and path-planning

NEEC Project Testbed

Robotic Testbed Vehicles: Segway RMP-200 and AscTech Pelican

The testbed is comprised of one Segway RMP 200 autonomous ground vehicle, one AscTech Pelican autonomous quadrotor, and several Parrot AR.Drone quadrotors.

The rationale for choosing a dual ground/aerial platform is that:

  1. These vehicles exhibit all of the challenges of a real autonomous unmanned system including: embedded system programming, sensing and perception, control and path-planning.
  2. Having a mixed asset ground-aerial vehicle platform exposes the students to significantly different vehicle dynamics, and also allows for training and learning in cooperative heterogeneous autonomous vehicle systems.
  3. Ground and aerial quadrotor platforms allow for easy on-campus experimental use.


Watch the video below to see the team's progress on autonomously landing the quadrotor on a moving target. The UAV detects the target with its onboard cameras before extracting relative pose information and performing the landing maneuver.