II.Parts and Devices
VI.How to play
Mecanum Wheel Robot Car Full Package (with 18650 batteries)
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The above robot cars are controlled by Arduino. If you have Raspberry Pi board, actually the robot car can also be controlled by Raspberry Pi. You can visit the following link to learn basic movement with Raspberry Pi.
Use Raspberry Pi to control Mecanum Omni wheel robot car – https://osoyoo.com/?p=31428
In this lesson, we will use Mobile to control our robot car and make an imitation driving. Since is a mock driving, we will use a virtual steering wheel and gear in our APP to imitate their counterparts in the real car.
OSOYOO Mecanum Wheels Robotic Car Chassis x 1 (2xleft-wheels/2xright-wheels and Motor x 4)
OSOYOO Mega2560 board, fully compatible with Arduino x 1
OSOYOO Wi-Fi shield x 1
OSOYOO Model Y motor driver x 1
OSOYOO HC02 Bluetooth module
OSOYOO MG90 servo motor x 1
OSOYOO Ultrasonic sensor module x1
OSOYOO Ultrasonic mount holder
OSOYOO Battery box x 1
OSOYOO 3pin female to female jumper wire x1
OSOYOO 6pin male to female jumper wire x2
OSOYOO 2 pin XH.25 female to female x1
OSOYOO 10 pin jumper wire male to female x1
18650 Batteries(3.7V) x 2
You must complete lesson 1 (assembling the car) before you continue on with this lesson.No need to change anything, just keep the hardware wire connection as it is.
(Note: You need to split 2 pcs of male-to-female jumper wires from our 10-pc jumper wire bundle. Any color from the bundle will be ok. The rest of 8 pcs wires are as spare parts for potential broken or damaged wires.)
Step2:Bluetooth Module should be inserted into Bluetooth 6-pin slot in OSOYOO Wi-Fi Board
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Step 1: Install latest Arduino IDE (If you have Arduino IDE version after 1.1.16, please skip this step). Download Arduino IDE from https://www.arduino.cc/en/Main/Software?setlang=en, then install the software.
Step 2: Download https://osoyoo.com/driver/mecanum_metal_chassis_m2/m2-lesson4.zip, unzip the download zip file m2-lesson4.zip, you will see a folder called m2-lesson4.
Step 3: Connect Mega2560 board to PC with USB cable, Open Arduino IDE → click file → click Open → choose code “m2-lesson4.ino” in m2-lesson4 folder, load the code into Arduino.
Step 4: Choose corresponding board/port for your project, upload the sketch to the board.
Go to your Google Play or Apple APP store and search APP name “OSOYOO imitation driving”, Download the APP as following and install it in your smartphone.
Power on the robot, and open APP.
1)Connect APP to HC-02 Bluetooth Module
2)Click Engine Switch to start/stop the car
3)Click Speed +/- button to accelerate or reduce speed
4)Rotate the mobile phone to change direction (steering wheel will rotate while you are turning the phone).
5)click Gear button to change gear to Forward or Backward direction.
6)press F1 to Shift to left way, F5 to shift to right way, F3 to up left diagonal, F4 to up right diagonal.
To get better running performance result, motor power (speed) value should be adjusted properly as per battery level. If motor power (speed) value is too high, your car might run too fast and easy to out of control. If motor power (speed) is too low, the car might not even move.
To adjust the motor power value, you need to change the 3 constants line 24,25,26,27,28 in m2-lesson4 sketch file:
#define MAX_SPEED 150 #define MIN_SPEED 70 #define TURN_SPEED 120 #define SLOW_TURN_SPEED 80 #define BACK_SPEED 90
MIN_SPEED is the minimum power required to start the car. If when APP engine toggle is switched to RED, but your car does not move, you need to increase this value, if the car runs too fast at engine start moment, you need to reduce this value.
TURN_SPEED, SLOW_TURN_SPEED value determines the turning speed of your car. If your car turning too fast, you need to reduce these two values, if turning too slow or not turning, increase these two values. Always make SLOW_TURN_SPEED about 20 to 40 lower than TURN_SPEED value.
BACK_SPEED value determines the reverse back running speed.
After batteries are running low, you might need to increase the value of these 3 constants. You can gradually add or reduce 10 each time on these values and compare which values have best tracking performance.
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