Code and configuration files for a chess playing enhancement to a remote presence robot!
The root directory contains some frequently requested design documents and plans as PDFs, plus the index.html that defines the HTML that is the root page of the end user app.
Chess profiler by the amazing Maris Van Sprang!
JSON configuration files for IBM Watson Assistant workspaces
CSS files for end user interface largely generated and maintained by Ionic
|moving_avg_net.js||Generated neural net that runs on the Espruino; generates a moving average of readings|
|back_panel.js||Controller for the back planel IR sensors, switches and touch sensors|
|sensors_LIDAR_ears.js||Controller for the LIDAR ears that are used to see in front of the robot. The program combines the function to move the ears, alongside the ability to read the servo potentiometer to work out which direction they are facing and to read the distance readings from the LIDAR itself|
|ears only_test.js||Simple controller for the ear servo motors only (no LIDAR)|
Visuals for end user interface, includes default camera image and SVG for Sensors tab. Some reference images of the hero prop are also included.
|app.js||Basic structure of the application modules plus some low level functions|
|controllers.js||Each tab has its own controller in this file that respondes to user events and manipulates the model. This separation of event handling and model manipulation makes maintenance and problem diagnosis easier.|
|directives.js||There are custom directives for the locked/unlocked icon on each tab (that shows whether communications between browser and dog are working in both directions) and the joystick on the Motors tab. These directives make the HTML much easier to understand and maintain.|
|services.js||The shared services maintain a model of the state of the dog in the front end app; they also support the creation of sockets between the app and dog and the standardisation of messages flowing over that connection. The translation between sensor readings and the SVG world are also calculated here for display on the sensors page.|
This directory contains the high level descriptions, models and schematics for K9. It also provides 3D models in SketchUp and TinkerCAD/3d printing formats to enable the recreation of components.
This directory contains the flows to control K9. It provides the means to flow information between the various elements of the dog and co-ordinates movement and speech. It also contains the definition of the dashboard to show on K9's screen.
This directory contains the python programs that use the Adafruit PWM Servo Driver and RoboClaw PID MotorController to make K9 move. A harness is included to generate sensor data to simulare collisions. There are also some simple scripts to interface to Watson Conversation and STT (and to K9's espeak TTS)
|K9PythonController.py||RoboClaw based Motor Controller|
|ear_controller.py||Controls K9's ears to collect forward facing LIDAR information|
|logo.py||Translates simple Logo paths into a movement plan for the RoboClaw|
|memory.py||Provides access to K9's short term memory which stores state and sensor readings|
|status.py||Sends K9's current state to node-RED (and browser) as JSON string every 200ms|
|K9_roboclaw_init.py||Stores PID and motor settings in Roboclaw NVRAM|
|node_RED_harness_ultrasonic.py||Creates simulated LIDAR, IR and ultrasonic sensor readings|
|ttsrobot.py||Uses Snowboy, Watson STT, Conversation and TTS - a bit Alexa like :+)|
Simple deployment scripts to move code into right place on the Pi
This directory contains the HTML for each of the tabs of the user interface (including the definition of the tabs themselves!). Keeping the html for each tab separately simplifies testing and maintenance.
Tessel is not currently used on the K9 robot