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Rubyik's Cube by Stafford Brunk The Rubik's Cube is one of the world's most recognizable puzzles. Knowing how to solve a scrambled cube can almost be called a badge of honor. While there are a multitude of books, articles, and apps on how to solve a cube as a human, what does it take to have a computer solve the problem? This talk will dive into exactly that question. We'll start with an overview of Rubik's Cube algorithms, move onto the logistics of implementing these algorithms, and finish up with some real examples of using Ruby to solve a Rubik's Cube!
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In this talk titled 'Rubyik's Cube,' Stafford Brunk explores the intersection of programming and Rubik's Cube solving. He provides an overview of Rubik's Cube algorithms and demonstrates how to implement these algorithms using Ruby to solve the cube. The talk begins with Brunk's personal anecdote about how a conversation with neighbors sparked his interest in building a Rubik's Cube-solving robot, despite being a novice at solving the cube himself. He lays out a roadmap for the presentation, starting with the basic terminology and movement notation essential for understanding Rubik's Cube mechanics. Key Points Discussed: - **Terminology and Structure of the Cube**: Brunk explains the essential terms related to the Rubik's Cube, such as faces, facelets, and cubelets, along with the significance of orientations. - **Movement Notation**: He introduces the notation system for cube movements, which details how cubers communicate rotations, and how this notation can be used to represent complex sequences of movements. - **Solving Strategies**: He outlines three main strategies to solve the cube: brute force, CFOP (Cross, First Two Layers, Orientation, Position), and Kociemba's two-phase algorithm, highlighting the efficiency and feasibility of each method. - **Complexity of the Cube**: The talk delves into the vast complexity of the cube, noting that there are 43 quintillion potential permutations, stressing the importance of optimization techniques over brute-force computation. - **Kociemba's Algorithm Demonstration**: Brunk employs Kociemba's algorithm, explaining its two-phase approach which allows for efficient solutions. He illustrates the programming aspect of the algorithm through live coding, aiming to minimize the move distance required to solve the cube. - **Future Directions**: The talk concludes with Brunk's plans for optimizing the implementation, enhancing the robot's functionality, and developing a detailed guide for building a Rubik's Cube-solving robot, which includes using OpenCV for state recognition and programming stepper motors for precise cube manipulation. The presentation effectively marries programming with practical robotics, providing insights for those interested in algorithm development and cube-solving technologies.
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