The Fastest Maze-Solving Competition On Earth

Veritasium

24 May 202325:22

EducationalLearning

32 Likes 10 Comments

TLDRThe video explores the history and evolution of Micromouse, a robotics competition where small robots race to solve mazes. It started in the 1970s, inspired by early AI experiments. Though once considered solved, innovations like diagonal movement and vacuum downforce have pushed Micromouse to new speeds and complexities. Core concepts like search algorithms and real-world engineering challenges keep enthusiasts engaged today. Micromouse exemplifies how a simple robotics challenge continues posing rich problems by combining software, hardware, and emerging technologies.

Takeaways

🐭 The Micromouse competition challenges participants to build autonomous robots that navigate mazes as quickly as possible, highlighting the intersection of robotics, engineering, and programming.
🏆 Competitors from around the world vie for honor and recognition, with victory margins as slim as 20 milliseconds, showcasing the intense competitiveness and precision engineering involved.
📈 The origin of Micromouse dates back to Claude Shannon's Theseus, an electronic mouse from 1952, demonstrating early concepts of machine learning and inspiring the field of AI.
🚀 Innovations in Micromouse include autonomous navigation without GPS or internet, fitting all necessary technology within a small frame, emphasizing engineering creativity and constraints.
📍 The competition's mazes are designed with complexity and unpredictability, requiring sophisticated strategies and algorithms for efficient and fast navigation.
✏️ Flood fill algorithms represent a popular strategy among participants, illustrating the blend of optimism and adaptability in navigating the mazes.
🔮 The evolution of Micromouse has seen technological advancements like the introduction of vacuum fans and gyroscopes, pushing the boundaries of speed and control.
🛠 Significant 'Fosbury flop' moments in Micromouse history have led to paradigm shifts in design and strategy, such as the implementation of diagonal movements and sweeping turns.
⛓ Micromouse remains a vibrant and evolving field, despite predictions of its decline, with ongoing innovations and the introduction of new challenges like quarter-size mice.
💡 The enduring appeal of Micromouse lies in its ability to combine various engineering disciplines into an accessible and competitive format, encouraging continuous learning and innovation.

Q & A

What was the original inspiration for the Micromouse competition?
-The original inspiration was a misunderstanding - IEEE editors heard about a competition for 'electronic mice' in France, but it turned out to be battery powered mice, not intelligent robots. However, this misunderstanding inspired them to hold their own Micromouse competition starting in 1977.
What are the key rules and constraints for building a competitive Micromouse?
-The mouse must be fully autonomous with no remote control or assistance. It must fit within a 25cm x 25cm footprint, with no limit on height. It cannot fly or use combustion. The maze walls are 18cm across.
What are some basic maze solving algorithms used by Micromice?
-Early algorithms included depth-first search and breadth-first search. The most common modern approach is flood fill, where the mouse makes optimistic journeys drawing the shortest path to the goal, updating its map when it hits walls.
How did the introduction of diagonals change micromouse competition?
-Cutting diagonals instead of only orthogonal turns opened up many more route options, but required smaller chassis under 11cm wide. It also required new navigation algorithms to properly follow the walls.
What was the first major physical innovation that allowed faster speed?
-Using vacuum fans to generate up to 5x the mouse's weight in downforce, increasing friction and allowing it to turn at up to 6Gs without slipping.
How has the goal changed from just solving the maze to optimizing for speed?
-Once maze solving algorithms matured, competitors realized the fastest path was not always the shortest, leading to innovations for speed. The focus shifted to quick navigation over pure optimization.
How does Micromouse incorporate multiple fields of engineering?
-Micromouse requires skills in computer science/programming for navigation algorithms, electrical engineering for sensors/motors, and mechanical engineering for chassis design and mechanics. Optimizing the interaction of software and hardware is key.
Why are Micromouse competitions still advancing today?
-There are still innovations being made in chassis design, wheel configurations, sensors like computer vision, and navigation techniques. It combines software, hardware, and robotics in a complex optimization problem.
What is an example of a recent paradigm shift in competitive Micromouse design?
-Around 2010, vacuum fans went from a novelty to required equipment as builders realized the downforce enabled much faster cornering speeds without slipping.
What are some ways a beginner could start learning Micromouse without advanced tools?
-At its core, Micromouse is about a mouse solving a maze. Beginners can start with simple maze solving algorithms before worrying about speed optimizations. Many components can be easily purchased and assembled.

Outlines

00:00

😊 The Fascinating History Behind Micromouse Competitions

The first paragraph gives background on Micromouse competitions, which involve small autonomous robots navigating mazes. It describes the original inspiration in 1952 from Claude Shannon's electronic mouse named Theseus, traces the misunderstood origins of the IEEE competition in 1977, and conveys the excitement and global spread of Micromouse contests.

05:02

😲 Innovative Micromouse Search Strategies and Algorithms

The second paragraph examines various maze-solving algorithms employed by Micromice, including depth-first search, breadth-first search, exhaustive search, and flood fill. It explains why flood fill emerged as a preferred strategy, allowing mice to efficiently map the maze and find shortest paths.

10:04

🤯 Micromouse Contests Constantly Pushing the Limits of Innovation

The third paragraph counters the notion that Micromouse contests had become solved by the late 1980s. It highlights innovations like diagonal movement and propeller fans that allowed smaller, faster mice, completely changing how they navigate mazes. Ongoing advances in sensors, motors, and computing show Micromouse competitions continue driving cutting-edge robotics.

15:06

😮‍💨 Navigating Tricky Maze Features Requires Careful Control

The fourth paragraph examines the importance of precision and control for Micromice traversing mazes at high speeds. It compares the centripetal forces involved to race cars on banked turns and explains how competitors overcame friction limitations by vacuuming mice to surfaces with propeller fans.

20:06

🤩 Modern Micromice Blend Software, Hardware, and Creativity

The fifth paragraph emphasizes how modern champion Micromice artfully combine programming, electronic components, creative chassis and wheel configurations into integrated robotic systems. This blend of software, hardware, and human ingenuity keeps competitions dynamic, with room for new innovations like omnidirectional control or computer vision.

25:06

😊 Get Started with Your Own Micromouse Creation

The final sponsorship paragraph encourages viewers to build their own Micromice using Onshape's free online 3D CAD platform. It highlights Onshape's real-time collaboration and version control features for efficient hardware design and open source projects.

Mindmap

Keywords

💡Micromouse

Micromouse is a robotics competition where small robot 'mice' have to navigate through a maze autonomously. It relates to the video's theme of problem solving and innovation in robotics. The script mentions the origins of the competition in trying to build an electronic mouse successor to 'Theseus', and how the competition spread globally over decades, while innovators kept pushing the limits of speed and maze solving algorithms.

💡autonomous

Autonomous means the micromice have to navigate the maze fully independently, without any remote control or external guidance. This constraint is core to making the competition a test of robotics intelligence and innovation. The script notes rules prohibiting things like GPS or nudging the mice.

💡flood fill algorithm

The flood fill algorithm is a key maze solving approach used by competitive micromice. It involves the mouse mapping the maze optimistically at first by assuming no walls, then 'flooding' updated distance values across the maze map whenever it hits a wall. This allows efficient searching driven by following the lowest numbers. The script highlights how flood fill became a dominant strategy.

💡diagonal movement

Cutting across maze corridors diagonally was an early innovation that changed micromouse competition, opening up many more path options. The script notes how this was initially seen as risky and required new navigation algorithms, but soon became widespread as mice could move faster with fewer turns.

💡friction

Friction between the micromouse wheels and floor became a key limiting factor in speed and control, with mice slipping uncontrollably at high speeds before further innovations. This relates to physics concepts governing turning forces. The script highlights the dust tape competitors use to reduce friction.

💡vacuum fan

A major recent shift was the addition of vacuum fans to blow mice firmly downwards, increasing friction for turns up to 6Gs without slipping. This surprised many as an effective gimmick, allowing faster cornering. The script describes the vacuum fan mechanics in detail, allowing much greater speed.

💡paradigm shift

A paradigm shift refers to a dramatic change in core assumptions, technologies and approaches within a field. The script argues that innovations like diagonal movement, vacuum fans and others represented 'Fosbury flops' in micromouse - paradigm shifts advancing the competition versus just optimizing existing approaches.

💡mechanical upgrades

The video traces ongoing mechanical upgrades that allowed for innovations like diagonals and vacuum traction, from stepper motors to lighter sensors and chassis to DC motors with encoders and gyros for better control. This incremental improvement of components expanded possibilities.

💡open source

The video's sponsor, Onshape, is promoted as helping collaboration in open source projects. The script argues Onshape's cloud-based real time CAD helps hardware developers adopt the collaborative agile methodologies common in open source software projects.

💡problem solving

At its core, the longevity of micromouse comes from it proving to be a deceptively complex problem solving challenge. The script bookends this message, noting how micromouse involves optimizing software, hardware and their interaction - persisting as an arena for innovation.

Highlights

Proposes a new method for detecting credit card fraud using machine learning techniques.

Found that random forest models had the highest accuracy for fraud detection compared to other classifiers.

Developed a model with 95% accuracy on detecting fraudulent transactions in a test dataset.

The model uses transaction metadata like purchase location, time, and amount to identify suspicious patterns.

Feature selection found that the day of week, transaction amount, and merchant category were most predictive.

Proposes an online learning approach to update the model continuously as new transactions occur.

Online learning improved fraud detection accuracy compared to batch retraining models.

The model achieved 90% recall in identifying fraud, with a low false positive rate of 5%.

Estimates a potential $2 million annual loss savings by using this model to detect fraud.

Limitations include biases in the transaction dataset and concept drift over time.

Future work could expand the model to include customer profile data for enhanced personalization.

The fraud detection model contributes a practical solution for an important real-world problem.

The techniques used could be extended to other domains like intrusion detection or anomaly detection.

Provides useful insights and methods for applying machine learning to fraud analysis.

Overall an innovative and technically strong study on an important topic with practical business impacts.

Transcripts

Browse More Related Video

How Far is Too Far? | The Age of A.I.

2024 AI : 10 Things Coming In 2024 (A.I In 2024 Major Predictions)

MIT 6.S191 (2023): The Future of Robot Learning

The Economy of Tomorrow | Aging Future | Documentary Economy

How Nvidia Grew From Gaming To A.I. Giant, Now Powering ChatGPT

Why Are People Having Less Sex Now Than Ever Before?