For context, micromouse is a competition where robots complete to solve mazes of varying pattern but standardized size by driving through them with no guidance or compute offboard of the robot itself. Historically the mazes were 3 meter squares composed of a 16 x 16 grid of cells, each 180mm on a side and 50mm tall, which puts bounds on the size of the robots involved.
What are the hallmarks of a [Keri] micromouse design? Well this is micromouse, so everything is pretty small. But [Keri]’s attention to detail in forming miniaturized mechanisms and 3D structures out of PCBs really stands out. They’ve been building micromouse robots since 2016, testing new design features with each iteration. Versions three and four had a wild suction fan to improve traction for faster maneuvering, but the KERISE v5 removes this to emphasize light weight and small size. The resulting vehicle is a shocking 30mm x 32mm! We’re following along through a translation to English, but we gather that [Keri] feels that there is still plenty of space on the main PCBA now that the fan is gone.
The processor is a now familiar ESP32-PICO-D4, though the wireless radios are unused so far. As far as environmental sensing is concerned the v5 has an impressive compliment given its micro size. For position sensing there are custom magnetic encoders and a 3 DOF IMU. And for sensing the maze there are four side-looking IR emitter/receiver pairs and one forward-looking VL6180X laser rangefinder for measurements out to 100 or 150mm. Most of these sensors are mounted on little PCB ‘blades’ which are double sided (check out how the PCB shields the IR emitter from it’s receiver!) and soldered into slots perpendicular to the PCBA that makes up the main chassis. It goes without saying that the rest of the frame is built up of custom 3D printed parts and gearboxes.
If you’d like to build a KERISE yourself, [Keri] has what looks to be complete mechanical, electrical, and firmware sources for v1, v2, and v3 on their Github. To see the KERISE v5 dance on a spinning sheet of paper, check out the video after the break. You don’t want to miss it!
Dr. Claude E. Shannon was born 100 years ago tomorrow. He contributed greatly to the fields of engineering, communications, and computer science but is not a well known figure, even to those in the field. However, his work touches us all many times each day. The network which delivered this article to your computer or smartphone was designed upon important theories developed by Dr. Shannon.
Shannon was born and raised in Michigan. He graduated from the University of Michigan with degrees in Mathematics and Electrical Engineering. He continued his graduate studies at Massachusetts Institute of Technology (MIT) where he obtained his MS and PhD. He worked for Bell Laboratories on fire-control systems and cryptography during World War II and in 1956 he returned to MIT as a professor.
Shannon’s first impactful contribution was his masters thesis which took the Boolean Algebra work of George Boole and applied it to switching circuits (then made up of relays). Before his work there was no formal basis for the analysis of switching systems, like telephone networks or elevator control systems. Shannon’s thesis developed the use of symbolic notation to represent networks and applied simplifying rules to optimize the system. These same rules later translated to vacuum tube and transistor logic aiding in the development of today’s computer systems. The thesis — A Symbolic Analysis of Relay and Switching Circuits — was completed in 1937 and subsequently published in 1938 in the Transactions of the American Institute of Electrical Engineers.
Shannon’s doctoral work continued in the same vein of applying mathematics someplace new, this time to genetics. Vannevar Bush, his advisor, commented, “It occurred to me that, just as a special algebra had worked well in his hands on the theory of relays, another special algebra might conceivably handle some of the aspects of Mendelian heredity”. Shannon’s work again is revolutionary, providing a mathematical basis for population genetics. Unfortunately, it was a step further than geneticists of time could take. His work languished, although interest increased over time.
It’s off to the races once again with the Micomouse maze solving contest at the 2011 RoboGames. This is a picture of the winner, a bot called Min7 (main page) which was built by [Ng Beng Kiat]. Using four phototransistors and a flash sensor it managed to first map the contest maze, then speed run it in under four seconds. See both runs in videos after the break. He’s certainly got a leg up on the bots we saw last year. Min7 beats them both in time, and overall control during the speed run.
[Ng] mentions that this year is the first time he’s built a micromouse with four wheels instead of two. There’s a gyro on board which aids navigation by feeding the orientation data to the STM32 chip which controls the device. We took a moment to page through his past designs. It’s remarkable how they’ve evolved through the years. Continue reading “Micromouse Wins 2011 Maze Race In Under 4 Seconds”→
Micromouse competitions have been running in Japan since 1980. In all that time, the ruleset has remained essentially unchanged. The autonomous robot mouse navigates a 16×16 maze creating a map. It then determines the optimal solution for future runs. Current records are in the six to seven second range. Teams have had to find new ways to generate traction for better times. Momoco08 uses a fan to hold the mouse to the track surface. Embedded below you’ll find a video of it solving the maze plus a photo of the vacuum skirt.