In today's lesson, we selected a field that introduces a new challenge: it includes a skip section at a turn. To complete today's challenge, you can either modify the program provided in previous lessons or create a new one entirely on your own.
The next level of difficulty introduces self-crossing paths and bending lines. At this stage, we’ll create our first and simplest memory-based program.
For this challenge, it is assumed that the field layout is unknown before the competition, making it impossible to hardcode a specific sequence of turns.
The main difference between this field and the easier one is the addition of crossroads. Crossroads introduce a new level of difficulty that can be overcome by programming the robot to remember the paths it has taken, although there are simpler and more elegant solutions.
For this challenge, it is assumed that the field layout is unknown before the competition, making it impossible to hardcode a specific sequence of turns.
The main takeaways from today's lesson are how to alternate between following a line and performing other actions needed to complete the basic level of the line-following challenge, and how to plan your program ahead of time. Today's program will serve as a foundation to build upon for solving more advanced line-following challenges.
Then the problem lies in other external factors.
PID is the most popular method for programming line-following robots. It’s a bit complex, so this tutorial is longer, as we’ll break it down into steps and explain each element of the equation.
This approach to programming line-following robots is not ideal for beginners. Attempting to learn this as a first step in competition preparation may give a misleading impression of the competition's complexity and could discourage students from learning the necessary skills to compete in this category.
Wheel condition plays a crucial role in the performance of any robot, so it’s common practice to maintain your robot before testing and especially before a competition. Here are some steps you can take to ensure that any variations in the robot’s performance aren’t due to the wheels:
Securely dock the ship that contains the samples and artifacts your team has collected.
Collect samples and artifacts from around the mat so they can be analyzed by scientists in the lab.
Adjust the cargo ship’s route to safely avoid whale migration routes by moving to another shipping lane.
Krill are a whale’s favorite food! Collect the krill and feed them to the hungry whale.
Use the ship’s sonar technology to scan the surroundings for nearby objects or animals.
Some waters are too difficult to reach with larger ships. Send the submersible to explore the opposing field’s waters.
An unknown creature has attached itself to the AUV! Safely release it and deliver it to the cold seep.
Rearrange the artificial habitat stacks to create safe homes for the crabs and other sea creatures in this area.
Retrieve the chest from the shipwreck to reveal the history and treasure it holds.
Raise the mast to restore the sunken shipwreck and explore what is inside.
Guide the angler fish back to its unexpected home within the shipwreck.
Help the scuba diver transport new coral from the nursery to the reef.
Carefully mount the new coral structure without damaging other nearby reef segments.
The shark was just tagged for research - release it back into its habitat.
Secure new coral structures to grow in the nursery until they are strong enough for transport to the reef.
While "multistate line following" can describe a variety of algorithms, this tutorial will cover its implementation using the ducky line-following method.
This is the most basic line-following method, commonly known as the "ducky" line-following method.
