The Vision Of ZenoRobotics
Meet Peter J. Zeno
CEO @ ZenoRobotics
Boise, Idaho, U.S
Peter J. Zeno is the CEO of ZenoRobotics, LLC. He received his Master of Science degree in Electrical Engineering from Johns Hopkins University and a Ph.D. in Computer Science and Engineering from The University of Bridgeport.
Peter is interested in the hardware, software, and algorithm design of autonomous mobile robots, as well as artificial intelligence that mimics how the brain works.
He has spent over 25 years in the industry performing hardware and software design for major defense contractors.
What inspired you to pursue a career in robotics?
While still searching for a Ph.D. thesis topic, I had built a basic object avoidance mobile robot for a class I was taking. My student-professor kept pushing my creativity by asking “how was the robot’s capabilities unique?”.
Several design iterations of adding more capabilities to my robot led to having my robot go out and explore its environment, then after several turns due to object/walls in the way, have it try to come back to its exact starting location using simple vector math.
I was, therefore, emulating a pseudo-foraging action. This is how I picked up key concepts such as path integration, homing, and how these were accomplished not only by animals but by humans traveling across the oceans, way before the existence of GPS technology.
Where ship captains navigated using the stars, as well as other measurements taken.
What is the story and vision of ZenoRobotics?
Being the inquisitive person I am, I pondered how navigation and path integration was accomplished by animals. Luckily, there has been much research done in this area pertaining to rodents.
This is how my Ph.D. thesis evolved into a neurophysiological based navigation system for autonomous mobile robots (AMRs), and my development of the “ratbot”.
The ratbot emulates the functionality of the specialized neurons used for spatial awareness and navigation found in the hippocampus and nearby entorhinal cortex.
When I heard of the DARPA Subterranean Challenge, I was instantly hooked into wanting to compete in it. I love challenges, as well as learning.
Thus, my research into what type of architectures were best suited for the various circuit environment evolved.
I realized that this venue was an awesome opportunity to getting name recognition for a startup company (or any company, university, etc.) if my robots made it into the competition, and what a great way to make a living at doing what I love.
I have been a maker, experimenter, and pseudo-scientist since I was a child.
My vision for ZenoRobotics is to make the best and more neurophysiological based autonomous mobile robots, as well as educating others who are interested in robotics along my journey.
Explain one case were your robots are implemented and its value?
The first major robot that ZenoRobotics is currently working on, and we hope to have a prototype in use at a nearby hospital or elderly care facility shortly, is an AMR equipped with an ultraviolet C light.
The need for such a robot has become apparent due to the COVID-19 pandemic.
Thus, instead of installing systems in every patient’s room, which would be very costly, or have someone dedicated to moving a portable system around, why not have the robot go where it needs to on its own.
This saves time, money and the robotic system can also generate a cleaning log that the hospital can use.
Describe one challenge robotics is facing for their use and development?
The artificial intelligence involved in robotics is very much lagging. The developer must make sure the program for every possible scenario that may arise.
Additionally, visual processing systems certainly have come a long way with image recognition and distance sensing.
However, there is much more information that can be extrapolated from scenes. More than 50 percent of the cortex, the surface of the brain, is devoted to processing visual information.
We have only scratched the surface when it comes to getting the most out of visual data, along with other sensory fusion.