KyivJS: control of mobile robots with JavaScript

Beginning: Arduino Inventor's Kit

ReadBoard Key features

• Based on Arduino Uno
• ATmega328 microcontroller
• 32k Flash Memory
• 16MHz Clock Speed
• Input voltage - 7-15V
• 14 Digital I/O Pins (6 PWM outputs)
• 6 Analog Inputs
• USB connection

C++ Blink example

        int ledPin =  13;    // LED connected to digital pin 13
         
        // The setup() method runs once, when the sketch starts
         
        void setup()   {                
          // initialize the digital pin as an output:
          pinMode(ledPin, OUTPUT);     
        }
         
        // the loop() method runs over and over again,
        // as long as the Arduino has power
         
        void loop()                     
        {
          digitalWrite(ledPin, HIGH);   // set the LED on
          delay(1000);                  // wait for a second
          digitalWrite(ledPin, LOW);    // set the LED off
          delay(1000);                  // wait for a second
        }
            

JavaScript Blink example

        var j5 = require("johnny-five");
        var myBoard, myLed;

        myBoard = new j5.Board();

        myBoard.on("ready", function() {

          myLed = new j5.Led(13);

          myLed.strobe( 1000 );

          // make myLED available as "led" in REPL

          this.repl.inject({
              led: myLed
          });

          // try "on", "off", "toggle", "strobe", "stop" (stops strobing)
        });
              

Johnny-Five

"... is an Open Source, IoT and Robotics programming framework"

• Arduino
• Beagle Bone
• Intel Galileo
• Raspberry Pi
• many more

Johnny-five interfacing with Arduino

First try: Motobot

Hardware

• Arduino Uno
• Motor Shield
• Ultrasonic distance sensor
• Servo

Software

• Johnny-Five
• Standard Firmata
• Naive obstacle avoidance algorithm

Coursera

Course content

• Control theory, linear algebra
• Different behaviors
• Real robot control

Driving robots around

Divide and conquer with Behaviors

• Go-to-goal
• Avoid-obstacles
• Follow-wall
• Track-target

Differential Drive Robots

• In order to control mobile robots, we need models
• Differential drive wheeled robots a very common

Differential Model

Unicycle Model

Model 2.0

Odometry

• The state of the robot is (x, y, φ)
• How do we obtain this state information?
• Two possibilities:
  • External sensors
  • Internal sensors
    • Orientation: Compass
    • Position: Accelerometers, Gyroscopes
    • Wheel Encoders

Wheel Encoders

• Wheel encoders give the distance moved by each wheel
• Assume the wheels are following an arc (short time scale)

How it looks?

Wheel Encoders

Special thanks

Range sensors

Robot communication control

Alternative simulator

Communication interface

              
    Command Set:
    ==========================  ===============================================
    $CHECK*\n                   returns 'Hello from QuickBot'
    $PWM?*\n                    returns wheel speeds in PWM: [50, -50]\n
    $PWM=[-100,100]*\n          sets the speed of the robot wheel velocities
    $ENVAL?*\n                  returns the encoder ticks ``(tl, tr)`` tuple
    $ENVEL?*\n                  returns the encoder velocities ``(vl, vr)``
                                tuple
    $IRVAL?*\n                  returns the 5-tuple raw ADC values of the IR
                                sensors, e.s [80.0, 251.0, 234.1, 12.1, 21.3]\n
    $RESET*\n                   resets encoder position to zero
    $END*\n                     disconnects from socket
    ==========================  ===============================================
              
            

Pysimiam with Arduino

Challenges

• Testing on real hardware
• Bugs location
• Complex course material

Further steps

• Calibrate hardware
• Arduino Yun
• Obstacles avoidance
• Sim.I.am.js

Resources

• Control of Mobile Robots
• Using PySimiam in Coursera course
• O'Botics
• Slides
• Github repo of Quickbot-Five

Demo

Sensors

Go to goal

Thanks