Coastal Communities


Marauder Robotics

Building robot technologies to accelerate ocean ecosystem restoration and maintain balance

Team Lead

Dennis Yancey

RL RL Roof Lewis
SR SR Sergio Roberte

I have a part time job as well as studying so I don't have a lot of free time to write all my essays and assignments. When I first heard about this site, I was a little worried to use it but I decided to give a try and it was the best thing I did. Got the grades I was expecting and easy to communicate with the staffs too. Very happy!

AT AT Angy Trejo

Good luck!

Mr. Jeffrey Malcolm

I think this an innovative approach to solve the urchin problem. In regards to your solution, what AI technology are you using to convert your vision sensor data into actionable tasks for the robot?

Dr Dennis Yancey Jr.

Thanks Jeff!

MarauderONE is using machine learning in the following ways:

1) Identify/infer, quantify, and map ecosystem biodiversity.
2)Stitch together a comprehensive ecosystem map from acquired images and video.
3) Determine best navigational path for hardware to engage target urchin based on prevailing environmental conditions.
4) Determine the optimal sequence of movements to acquire target based on equipment constraints and environmental conditions.
5) Determine optimal restoration path that minimizes energy consumption and maximize effective coverage are in the field of operation
6) There are way too many to disclose!

Dr. Alexander Dale

In response to Our solution goals over the next 12 months:

Can you add more details on the current state of the hardware (prototypes built, deployed, etc.)?

Dr Dennis Yancey Jr.

Thank you Dr. Dale!

MarauderONE development occurs in four distinct technology modules.
1)Hardware/Navigation - MarauderONE uses modified hardware from previous field projects. The 0-6m goal is to tailor the form and function of engaging urchins.
2)CV/Inference - Running algorithm on android using TensorflowRT. Tested on aquarium exhibits. The algorithm has high inference certainty. The 0-6m goal is to optimize the algorithm to recognize urchins, starfish, kelp, crabs, lobsters, abalone, fish, and otters.
3)Engagement - It is in the Design phase. The 0-6m goal is to build and test prototypes in the field.
4)Power - Built prototype. The 0-6m goal is to check the prototype in the lab and optimize the design for energy production and manufacturability.

In 6-12m, we want to test a fully integrated MarauderONE in the field in CA and AUS.

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