Introduction

Welcome to this tutorial on navigation and control in robotics. In this tutorial, we will explore the various methods used for navigating and controlling robots, with a focus on programming aspects.

By the end of this tutorial, you will:
- Understand the basic concepts of robot navigation and control
- Learn how to implement simple navigation and control algorithms
- Be familiar with some best practices in robotics programming

Prerequisites: Basic understanding of programming logic and mathematics. Experience with Python is beneficial but not mandatory.

Step-by-Step Guide

Robot Navigation

Robot navigation is about making a robot move from one point to another autonomously. This generally involves three main steps:
1. Perception: The robot needs to understand its surroundings. This is usually done using sensors.
2. Localization: The robot needs to know its position within its environment.
3. Path Planning: The robot needs to plan a path from its current location to its target location.

Robot Control

Robot control is about making a robot perform specific actions or behaviors. This mainly involves two types of control systems:
1. Open-Loop Control: The control action from the controller is independent of the "process output", which is the system variable that is being controlled. It does not use feedback to determine if its output has achieved the desired goal.
2. Closed-Loop Control: This system monitors the output of a system and adjusts the input based on this monitoring, using a 'feedback' loop.

Code Examples

Let's look at some practical examples in Python:

1. Open-loop control: This simple example moves a robot forward at a constant speed.

# Define the speed
speed = 10  # units per second

def move_forward():
  # Move the robot forward at the specified speed
  robot.set_speed(speed)

# Call the function to move the robot
move_forward()

1. Closed-loop control: This example moves a robot to a specific target location using a feedback control loop.

# Define the target location
target_location = 50  # units

def move_to_target():
  # Current location of the robot
  current_location = robot.get_location()

  # Error between the current and target location
  error = target_location - current_location

  # Control input proportional to the error
  control_input = 0.1 * error

  # Move the robot forward using the control input
  robot.set_speed(control_input)

# Call the function to move the robot
move_to_target()

Summary

In this tutorial, we've learned about the basics of robot navigation and control. We've looked at how robots perceive their environment, localise themselves within it, and plan their paths. We've also covered open-loop and closed-loop control systems.

For further study, consider exploring more complex navigation algorithms like SLAM (Simultaneous Localization and Mapping) and more sophisticated control systems like PID controllers.

Practice Exercises

1. Write a function to make the robot move in a square pattern using open-loop control.
2. Modify the closed-loop control example to make the robot stop when it reaches the target.
3. Implement a simple obstacle avoidance behavior. The robot should stop or change direction if it detects an obstacle in its path.

Solutions and Tips

1. To make the robot move in a square, you can call move_forward() for a certain duration, then make the robot turn 90 degrees, and repeat this process 4 times.
2. To make the robot stop at the target, you can add a conditional statement in move_to_target() that sets the speed to 0 if the error is less than a small threshold.
3. For obstacle avoidance, you can use the robot's sensors to detect obstacles. If an obstacle is detected, you can change the robot's direction by a certain angle and continue moving.