In this tutorial, we will explore templates and macros in C++.

Prerequisites

• You have completed this tutorial: How to Use Lambda Expressions and File I/O in C++.
• I am assuming you are using Visual Studio Code, but you can use any code editor.

Employing Macros

Let’s explore how to use macros in C++ and their application in robotics projects. Macros are preprocessor directives that allow you to define reusable pieces of code, processed before compilation. 

Open a terminal window, and type this: 

cd ~/Documents/cpp_tutorial && code . 

Create a new C++ file and name it basic_macro.cpp.

Type the following code into the editor:

#include <iostream>

// Define a constant macro
#define PI 3.14159

// Define a function-like macro
#define AREA_CIRCLE(radius) (PI * (radius) * (radius))

int main() {
    double radius = 5.0;
    double area = AREA_CIRCLE(radius);

    std::cout << "The area of a circle with radius " << radius << " is: " << area << std::endl;

    return 0;
}

In this code, we define two macros:

1. PI is a constant macro that defines the value of pi.
2. AREA_CIRCLE(radius) is a function-like macro that calculates the area of a circle given its radius.

In the main() function, we use the AREA_CIRCLE macro to calculate the area of a circle with a radius of 5.0 and store the result in the area variable. We then print the calculated area using std::cout.

Run the code.

The output displays the calculated area of the circle using the AREA_CIRCLE macro.

It’s important to note that macros should be used sparingly and with caution, as they can sometimes lead to unexpected behavior if not used carefully. In modern C++, const variables, inline functions, or templates are often preferred over macros when possible.

Implementing Template Functions

Let’s explore template functions in C++, which allow us to write generic functions that can work with different data types. This is particularly useful in robotics when dealing with various sensor data types or mathematical operations. 

Create a new C++ file and name it template_functions_example.cpp. 

Type the following code into the editor:

#include <iostream>

template<typename T>
T find_max(T a, T b) {
    return (a > b) ? a : b;
}

int main() {
    std::cout << "Max of 10 and 20 is: " << find_max<int>(10, 20) << std::endl;
    std::cout << "Max of 5.5 and 2.1 is: " << find_max<double>(5.5, 2.1) << std::endl;
    return 0;
}

In this code, we define a template function find_max that takes two parameters of the same type and returns the greater of the two. The function uses the ternary operator to compare the two values. We then test this function with integers and doubles to show its versatility.

Run the code.

The output should display “Max of 10 and 20 is: 20” and “Max of 5.5 and 2.1 is: 5.5”, demonstrating how the template function adapts to different data types.

Defining Template Classes

Let’s explore template classes in C++, which allow us to create generic classes that can work with different data types. This is particularly useful for creating reusable data structures in robotics applications. 

Create a new C++ file and name it template_class.cpp.

Type the following code into the editor:

#include <iostream>

// Template class for a point in 2D space
template <typename T>
class Point {
private:
    T x;
    T y;

public:
    Point(T x, T y) : x(x), y(y) {}

    T getX() const { return x; }
    T getY() const { return y; }

    void printPoint() const {
        std::cout << "(" << x << ", " << y << ")" << std::endl;
    }
};

int main() {
    Point<int> int_point(5, 10);
    Point<double> double_point(3.14, 2.71);

    std::cout << "Integer point: ";
    int_point.printPoint();

    std::cout << "Double point: ";
    double_point.printPoint();

    return 0;
}

In this code, we define a template class called Point that represents a point in 2D space. The class has two private member variables, x and y, of type T. The typename keyword is used to specify that T is a type parameter.

The Point class has a constructor that takes x and y values and initializes the member variables. It also provides getter functions getX() and getY() to access the values of x and y, respectively. The printPoint() function is a member function that prints the point in the format (x, y).

In the main() function, we create two instances of the Point class: int_point with integer values and double_point with double values. 

We use the printPoint() function to print the points and verify that the template class works correctly with different data types.

Run the code.

The output displays the points created with integer and double values.

Template classes provide flexibility and help reduce code duplication, making the code more maintainable and efficient.

Thanks, and I’ll see you in the next tutorial.

Keep building!

In this tutorial, we will explore functions and pointers in C++.

Prerequisites

• You have completed this tutorial: How to Use Arrays, Vectors, and Strings in C++.
• I am assuming you are using Visual Studio Code, but you can use any code editor.

Using Mathematical Functions

Let’s explore how to use mathematical functions in C++ for robotics. Mathematical functions are essential for performing various calculations in robotic applications.

Open a terminal window, and type this:

cd ~/Documents/cpp_tutorial

code .

Let’s create a new C++ file and name it robot_math_functions.cpp.

Type the following code into the editor:

#include <iostream>
#include <cmath>

using namespace std;

int main() {
    double angle = 45.0;
    double radians = angle * M_PI / 180.0;

    double sine = sin(radians);
    double cosine = cos(radians);

    cout << "Sine: " << sine << endl;
    cout << "Cosine: " << cosine << endl;

    return 0;
}

In this example, we demonstrate how to use mathematical functions to calculate the sine and cosine of an angle.

First, we include the <cmath> header to use the mathematical functions. Then, we declare a double variable angle and assign it the value 45.0, representing an angle in degrees.

To convert the angle from degrees to radians, we multiply it by M_PI (which represents the mathematical constant pi) and divide by 180.0. We store the result in the radians variable.

To calculate the sine and cosine of the angle, we use the sin() and cos() functions, respectively. These functions expect the angle to be in radians. 

We pass the radians variable as an argument to these functions and store the results in the sine and cosine variables.

Finally, we print the values of sine and cosine using cout.

Run the code.

You should see the values of sine and cosine printed in the terminal.

In robotic projects, mathematical functions are commonly used for tasks such as calculating robot positions, orientations, sensor data processing, control algorithms, and motion planning.

Implementing Functions

Let’s explore how to implement functions in C++ for robotics. Functions are essential for organizing and reusing code in robotic applications.

Let’s create a new C++ file and name it robot_functions.cpp.

Type the following code into the editor:

#include <iostream>
#include <cmath>  // Added header for sqrt()
using namespace std;

// Function declaration 
double calculate_distance(double x1, double y1, double x2, double y2);

int main() {
    double distance = calculate_distance(0, 0, 3, 4);
    cout << "Distance: " << distance << endl;
    return 0;
}

// Function definition
double calculate_distance(double x1, double y1, double x2, double y2) {
    double dx = x2 - x1;
    double dy = y2 - y1;
    double distance = sqrt(dx * dx + dy * dy);
    return distance;
}

In this example, we demonstrate how to implement a function to calculate the distance between two points.

First, we declare the calculate_distance function before the main function. The function takes four parameters: x1, y1, x2, and y2, representing the coordinates of two points. It returns a double value, which is the calculated distance.

In the main function, we call the calculate_distance function with the coordinates (0, 0) and (3, 4). The returned distance is stored in the distance variable and then printed using cout.

After the main function, we provide the function definition for calculate_distance. Inside the function, we calculate the differences in x and y coordinates (dx and dy). 

Then, we use the distance formula (Pythagorean theorem) to calculate the distance between the points. 

Finally, we return the calculated distance.

Run the code.

You should see the calculated distance printed in the terminal.

In robotic projects, you can use functions for various purposes, such as calculating sensor data, controlling robot movements, implementing algorithms, and more.

Handling Pointers

Let’s explore how to handle pointers in C++ for robotics. Pointers are variables that store memory addresses and allow you to manipulate data directly in memory.

Let’s create a new C++ file and name it robot_pointers.cpp.

Type the following code into the editor:

#include <iostream>

using namespace std;

int main() {
    int robot_id = 42;
    int* ptr = &robot_id;

    cout << "Robot ID: " << robot_id << endl;
    cout << "Pointer Value: " << ptr << endl;
    cout << "Dereferenced Pointer: " << *ptr << endl;

    *ptr = 99;
    cout << "Updated Robot ID: " << robot_id << endl;

    return 0;
}

In this example, we demonstrate how to handle pointers to manipulate data in memory.

First, we declare an integer variable robot_id and assign it the value 42. Then, we declare a pointer variable ptr and initialize it with the address of robot_id using the address-of operator &. The & operator retrieves the memory address of a variable.

We print the value of robot_id, the value of ptr (which is the memory address), and the dereferenced value of ptr using the dereference operator *. The * operator, when used in front of a pointer variable, retrieves the value stored at the memory address pointed to by the pointer. This is called dereferencing.

Next, we use the dereference operator * to modify the value at the memory address pointed to by ptr. 

We assign the value 99 to *ptr, which effectively updates the value of robot_id. By dereferencing ptr and assigning a new value, we are changing the value stored at the memory address pointed to by ptr, which is the memory address of robot_id.

Finally, we print the updated value of robot_id to confirm that it has been modified through the pointer.

Run the code.

You should see the original robot ID, the pointer value (memory address), the dereferenced pointer value (which is the same as the original robot ID), and the updated robot ID printed in the terminal.

In robotics projects, pointers allow you to directly access and modify data without needing to move or copy it, which makes programs run faster and use less memory.

Managing Exceptions

Let’s learn how to manage exceptions in C++ for robotics applications. Proper exception handling is important for robust and reliable software systems, especially in the field of robotics where errors can have significant consequences.

Let’s start by creating a new C++ file called exception_handling.cpp.

Type the following code into the editor:

#include <iostream>
#include <stdexcept>

double divide(double a, double b) {
    if (b == 0) {
        throw std::runtime_error("Division by zero");
    }
    return a / b;
}

int main() {
    try {
        double result = divide(10, 0);
        std::cout << "Result: " << result << std::endl;
    } catch (const std::exception& e) {
        std::cerr << "Error: " << e.what() << std::endl;
    }
    return 0;
}

In this example, we define a function divide that throws a std::runtime_error exception if the denominator is zero. In the main function, we wrap the call to divide in a try block and handle any potential exceptions in the catch block.

Run the code.

You should see the error message “Error: Division by zero” printed in the terminal, as we intentionally passed 0 as the second argument to the divide function.

Proper exception handling is important in robotics applications, where unexpected situations or sensor failures can occur. By using exceptions and handling them appropriately, you can ensure that your code gracefully handles errors and maintains a consistent state, preventing potential damage or safety issues.

Thanks, and I’ll see you in the next tutorial.

Keep building!

In this tutorial, we are going to learn about one of the core concepts of object-oriented programming: classes and objects. 

Understanding how to use classes and objects is essential for structuring robust and maintainable code in robotics, where you often model real-world entities like robots, sensors, and actuators.

Prerequisites

• You have completed this tutorial: How to Handle Errors in Python.

Getting Comfortable with Classes and Objects

Let’s start by defining what a class is. Think of a class like a recipe for making cookies. Just as a recipe tells us what ingredients we need (these are called variables or attributes in programming) and what steps to follow (these are called methods or functions in programming), a class defines both the data and the actions that our program can use. The recipe itself isn’t a cookie – it’s just instructions, just like a class is just code until we use it.

An object is when you actually make the cookies using your recipe – in programming terms, we call this “instantiating a class.” When you just write down a recipe (define a class), you’re not using any real ingredients or kitchen space yet (no computer memory is used). But when you start baking (create an object), that’s when you use real ingredients and take up real counter space (the computer allocates actual memory for your object). Each batch of cookies you make from the same recipe is like creating a new object from your class – they use the same instructions but are separate, physical things in your kitchen (separate spots in computer memory).

Let’s create a simple class called Robot. This class will have some basic attributes like name and color, and a method that allows the robot to introduce itself.

Create a program called robot_class.py inside the following folder: ~/Documents/python_tutorial.

Write this code:

class Robot:
    def __init__(self, name, color):
        self.name = name
        self.color = color

    def introduce_self(self):
        print(f"Hello, my name is {self.name} and my color is {self.color}.")

The __init__ method is a special method called a constructor. It is called when a new object is instantiated, and it’s used to initialize the attributes of the class.

Now, let’s create an object of the Robot class:

r1 = Robot("Addison", "red")
r1.introduce_self()

This creates an instance of Robot named r1 with the name “Addison” and the color “red”. We then call the introduce_self method to make the robot introduce itself.

You should see the output:

This demonstrates how we’ve created a Robot object and used its method to perform an action.

Using classes and objects in robotics programming allows you to encapsulate behaviors and states associated with specific robotic components or subsystems, making your code more modular, reusable, and easier to manage. For example, each sensor or actuator can be modeled as an object with its methods for starting, stopping, and processing data.

Implementing a Basic Constructor

Let’s learn how to implement a basic constructor in Python, specifically within the context of robotics. 

Constructors are important for initializing robot objects with specific settings or parameters right when they’re created.

In Python, a constructor is defined using the __init__ method of a class. It is automatically invoked when a new object of that class is created.

The __init__ method can take parameters that define the initial state of the object. This is essential for robotics, where each robot might need specific configurations right from the start.

Let’s create a simple class called Robot. This class will have attributes such as name, type, and sensor_count, which we will set using the constructor.

Create a program called robot_constructor.py inside the following folder: ~/Documents/python_tutorial.

Write this code:

class Robot:
    def __init__(self, name, type, sensor_count):
        self.name = name
        self.type = type
        self.sensor_count = sensor_count
        print(f"Robot created: {self.name}, a {self.type} robot with {self.sensor_count} sensors.")

Here, the __init__ method initializes each new Robot instance with a name, type, and sensor count. These attributes allow us to differentiate between various robots, catering to different roles and functionalities in a robotics lab or factory.

Now, let’s create instances of our Robot class to see the constructor in action:

r1 = Robot("Atlas", "Humanoid", 5)
r2 = Robot("Spot", "Quadruped", 4)

This code creates two robots: “Atlas,” a humanoid robot with 5 sensors, and “Spot,” a quadruped robot with 4 sensors.

Now run this script.

You should see output indicating that the robots have been successfully created with their respective attributes. This output verifies that our constructor is working as expected, initializing each robot with its specific characteristics.

Overriding a Function

Let’s explore the concept of overriding functions in Python, particularly in the context of object-oriented programming. This technique is essential in robotics programming when you need different implementations of the same method in parent and child classes.

Let me explain how overriding works with an example from robotics. Imagine you have a basic robot (parent class) that can move and dock to a charging station. When you want to create a special type of robot (child class) that does these actions differently, that’s where overriding comes in.

In programming, overriding lets you take a behavior that already exists in a parent class (like how the robot moves) and give it a new set of instructions in the child class (like making a cleaning robot move in a specific pattern). It’s like saying “ignore the original instructions and use these new ones instead.”

Before we dive into overriding, you need to understand inheritance, which is how we create new types of robots based on our basic robot design. Just like a cleaning robot inherits all the basic features of the basic robot, a child class inherits all the code from its parent class.

Let’s create a base class called Robot. This class will have a simple method that describes the robot’s operation.

Create a file named function_override.py inside the following folder: ~/Documents/python_tutorial, and write this code:

class Robot:
    def action(self):
        print("Performing a generic action")

Here, our Robot class has one method, action, which prints a generic message about the robot’s activity.

Now, let’s create a subclass (also known as “child class”) called FlyingRobot that inherits from Robot class and overrides the action method to provide more specific behavior:

class FlyingRobot(Robot):
    def action(self):
        print("Flying")

In the FlyingRobot subclass, we redefine the action method. When we call the action method on an instance of FlyingRobot, it will print “Flying”, which is specific to flying robots, instead of the generic action message.

Let’s see this in action. We’ll create instances of both Robot and FlyingRobot and call their action method:

generic_robot = Robot()
generic_robot.action()  # This calls the base class method

flying_robot = FlyingRobot()
flying_robot.action()  # This calls the overridden method in the subclass

Save this script, and run it.

You should see this output:

This output shows how the action method behaves differently depending on whether it’s called on an instance of the Robot or the FlyingRobot.

Overriding methods is particularly beneficial in robotics when you deal with different types of robots that might share some functionalities but also have unique behaviors. By using overriding, you can ensure that each robot type performs its tasks appropriately while still inheriting from a common base class.

That’s it for this tutorial on function overriding. Thanks, and I’ll see you in the next tutorial.

Keep building!