Screen Shot 2018-11-06 at 5.05.42 PM.png
 

Building upon over 15 years of research at Carnegie Mellon University’s Robotics Institute

Founded by Dr. George Kantor, Tim Mueller-Sim, Tanvir Parhar, and Harjatin Baweja, Bloomfield Robotics is bringing our combined 30+ years of experience in designing and deploying robots in agricultural settings to the commercial space.

 

 
 

PROJECTS

FARMVIEW

In 20 years there will be 9.6 billion people to feed, and not enough food. Carnegie Mellon University's FarmView is tackling this problem through a team effort of researchers and robots that will increase crop yields with fewer resources by controlling and measuring the environment then analyzing the data, to provide solutions to farmers across the globe.

 

Ground-based Robot

At a base weight of 140 kg, the Robotanist is capable of carrying an additional 100 kg at up to 2 m/s for more than 8 hours between charges, thanks to the devotion of one-third of the base to a Li-Ion battery. With considerably lower ground pressure than the human foot and enough torque to drive straight up a wall, we've yet to get the robot stuck in the mud.

 

 

TECHNOLOGY

Sensors

Screenshot from 2016-08-03 23-25-58.png

A suite of navigation and phenotyping sensors give the robot a chance at navigating within the world. The robot comes standard with an RTK GPS, and aerospace grade inertial measurement unit, multiple navigation cameras, a Time of Flight sensor, and multiple LiDAR units. The modularity of the platform allows the inclusion of more sensors as the environment changes.

 

Computer vision, neural networks, and high-value crops

Merlot Grape Vineyard - Paso Robles, CA

Picture2.png

We've gained extensive experience over the past 8 years deploying custom-built camera systems through all sorts of high-value crops and extracting meaningful information from the captured images, including health, quality, and other important traits.

Through partnerships with growers associations, world renowned universities, and industry experts we've developed a wide range of algorithms for crops such as wine and table grapes, apples, and grain crops such as sorghum.

We then pass this high-level information back to the scientists, breeders, and cultivators so they can perform labor loading estimation for the year, determine problem areas in their fields, and help them breed better plants, faster.