Road to RubyKaigi: Play Hard(ware)

Road to RubyKaigi: Play Hard(ware)
2026.04.22. RubyKaigi 2026 LT

Transcript

1. Road to RubyKaigi: Play Hard(ware) @makicamel RubyKaigi 2026 2025.04.22.
2. About Me @makicamel / Maki Kawahara Loves Ruby , beer and sake Co-Organizer of PicoPicoRuby Creator of "Road to RubyKaigi"
3. Road to RubyKaigi 　 　 Road to RubyKaigi 　 https://github.com/makicamel/road_to_rubykaigi
4. Road to RubyKaigi A Ruby game by Rubyists, for Rubyists A side-scrolling action game played in the terminal Defeat bugs, escape deadlines, and make it to RubyKaigi
5. Road to RubyKaigi
6. PicoRuby
7. PicoRuby PicoRuby is very HOT at RubyKaigi 2026!
8. PicoRuby Ruby for embedded systems Runs on microcontrollers e.g. Raspberry Pi Pico 2W
9. Microcontroller Connect various I/O to build your own device
10. Acceleration
11. Acceleration What is acceleration? The rate of change of velocity e.g. A car starting to move: positive acceleration A car cruising at constant speed: acceleration is 0
12. Acceleration Acceleration Expresses changes in motion as numbers Lets us extract features and read movement 　 　 3-axis accelerometer module KXR94-2050 　 https://akizukidenshi.com/catalog/g/g105153/
13. Acceleration With an accelerometer, a human walking can make the game character walk!
14. Accelerometer 3 axes x: left-right y: front-back z: up-down Reads acceleration on each axis
15. Accelerometer Waveform while standing still Almost no change in acceleration
16. Accelerometer Waveform while walking Draws periodic arcs
17. Accelerometer Find patterns of change to read "motion"
18. Walk Detection
19. Walk Detection: Time Acceleration at a single moment A single point alone can't reveal "motion"
20. Walk Detection: Time Acceleration change over a time window "Moving" means changing over time Observe variation within the window
21. Walk Detection: Motion Intensity Amount of acceleration change in a time window = motion intensity How scattered the acceleration is
22. Walk Detection: Motion Intensity Condense acceleration change over a time window into a single number Represents motion intensity Still / walking become distinguishable Waveform information is lost Periodicity, rhythm of the wave Acceptable for this case If motion intensity exceeds a threshold, the player is "walking"
23. Walk Detection: Extracting Motion Intensity
24. Walk Detection: Extracting Motion Intensity 1. Extract motion intensity per axis 2. Sum the extracted values
25. Walk Detection: Per-Axis Motion Intensity e.g. Z axis
26. Walk Detection: Per-Axis Motion Intensity Mean mean = samples.sum / samples.size Deviation from the mean for each sample dev(n) = sample[n] - mean Squared deviation dev(n)² Mean of squared deviations (dev(1)² + dev(2)² + ... dev(n)²) / samples.size
27. Walk Detection: Per-Axis Motion Intensity Mean mean = samples.sum / samples.size Deviation from the mean for each sample dev(n) = sample[n] - mean Squared deviation dev(n)² Mean of squared deviations (dev(1)² + dev(2)² + ... dev(n)²) / samples.size
28. Walk Detection: Per-Axis Motion Intensity Mean mean = samples.sum / samples.size Deviation from the mean for each sample dev(n) = sample[n] - mean Squared deviation dev(n)² Mean of squared deviations (dev(1)² + dev(2)² + ... dev(n)²) / samples.size
29. Walk Detection: Per-Axis Motion Intensity Mean mean = samples.sum / samples.size Deviation from the mean for each sample dev(n) = sample[n] - mean Squared deviation dev(n)² Mean of squared deviations (dev(1)² + dev(2)² + ... dev(n)²) / samples.size
30. Walk Detection: Per-Axis Motion Intensity Motion intensity along the Z axis over the window
31. Walk Detection: Per-Axis Motion Intensity Motion intensity along X, Y, Z axes over the window
32. Walk Detection: Per-Axis Motion Intensity Sum the per-axis motion intensities def motion_intensity Math.sqrt(var(0) + var(1) + var(2)) end Motion intensity over the window
33. Walk Detection: Per-Axis Motion Intensity Walking starts when motion intensity exceeds the threshold class SignalInterpreter def walk_started? @window.motion_intensity > Config.start_threshold end
34. Walk Detection After this, add stop detection, running behavior, jump detection, and so on, done!
35. Demo
36. Special Thanks @youchan @pocke
37. Enjoy Creating!