FLL SuperPowered Judging Session Presentation - Robot Design - Lazer Robotics
Summary
TLDRLaser Robotics shares a five-year journey of robot design evolution, from an unbalanced, bulky model to a compact, efficient, and stable 13th version. They emphasize improvements in design, navigation, and programming, using Python for complex code and PID logic for error correction. The presentation highlights the use of passive mechanisms, gravity, and strategic design for mission efficiency, showcasing their success in completing 15 missions in 2.5 minutes with a high score.
Takeaways
- 🚀 The Laser Robotics team has been continuously improving their robot design over the past five years, with the Laserbot 13 being their latest iteration.
- 🔄 Each year, they learned from the inefficiencies of the previous design to enhance the next version, demonstrating a commitment to iterative improvement.
- 🏆 The team has achieved success in competitions, winning awards such as the robot design award in qualifiers and states, and the states in robot game and qualifier.
- 🔄 The design evolution focused on making the robot more compact, symmetric, and stable, with a lower center of gravity for better performance.
- 🛠️ The robot's design incorporates thin wheels, a compact form, durability, hidden wires, and symmetrical balance for field navigation and stability.
- 🔩 The robot's attachments are designed to be easily and efficiently attached and secured using gravity and upgraded facing axles, enhancing the robot's functionality.
- 🔧 The team uses passive mechanisms and 360-degree capabilities in their attachments to maximize the robot's efficiency and versatility.
- 💻 They have transitioned to using Spike Prime Python for programming, which allows for more complex code and better error correction.
- 🔍 The team implemented a PID logic system for error correction, which includes proportional, integral, and derivative components for smooth and accurate robot movement.
- 📊 They have a systematic approach to testing and selection, using performance scores based on success rates to choose the most practical and consistent hardware or software solutions.
- 🔄 The team's strategy includes leveraging line following and reducing travel distance to complete missions more efficiently, as demonstrated in their high-scoring performance in competitions.
Q & A
What is the main focus of the Laser Robotics presentation?
-The main focus of the presentation is to share the evolution of the Laserbot 13 design over five years and provide advice on how to improve robot charging sessions and overall robot performance.
How did the design of the Laserbot change from the first to the second year?
-From the first to the second year, the design of the Laserbot evolved from a bulky and unbalanced tutorial model to a more symmetric and balanced robot, although the charging port was over-engineered.
What was the significant improvement in the third year of the Laserbot's development?
-In the third year, the Laserbot was made completely original, extremely compact, allowing for easy drop-down attachments, and included hidden wires, which led to winning the robot and design award in qualifiers and states.
What adjustments were made to the Laserbot in its fourth version to improve its performance?
-In the fourth version, the Laserbot was made taller with a higher center of gravity, which resulted in winning the states in the robot game and qualifier.
What are some of the key features of the 13th version of the Laserbot?
-The 13th version of the Laserbot has improved stability with a lowered center of gravity, a systematic evaluation of its design, and it won the qualifier and states.
What dimensions does the Laserbot 13 have, and how do they contribute to its design?
-The Laserbot 13 has dimensions of 17 by 18 square inches, which, along with thin wheels and a compact design, contribute to its stability without sacrificing space.
How does the Laserbot 13 utilize color sensors for improved performance?
-The Laserbot 13 uses two color sensors for better field navigation, enhancing its ability to navigate and perform tasks on the field.
What is the advantage of the drop-on attachment system in the Laserbot 13?
-The drop-on attachment system in the Laserbot 13 is advantageous because it uses gravity for easy attachment and upgraded facing axles for secure locking, making it efficient and reliable.
What programming language and approach does the team use for the Laserbot's operation?
-The team uses Spike Prime Python for programming the Laserbot, which allows for more complex code and is a better alternative to block coding.
How does the team implement error correction in their robot's programming?
-The team uses a PID (Proportional, Integral, Derivative) logic system for error correction, which allows for maximum smoothness and accuracy in robot navigation.
What strategies does the team use to test and improve the Laserbot's performance?
-The team tests the robot's performance by conducting line navigation tests at different speeds and with or without attachments, recording the success rate and using it as a performance score to select the most practical and consistent options.
How do the team's design choices for attachments contribute to the efficiency of the Laserbot?
-The team uses passive mechanisms and designs attachments to utilize the 360-degree capabilities of the robot, employing gears that lock into place and motors for multiple functions, which increases the efficiency and versatility of the attachments.
What is the significance of using one-way doors in the Laserbot's design?
-One-way doors are used as a type of passive mechanism to lock onto objects or missions without the use of motors, providing an easy way to bring up or drop off units around the map.
How does the team ensure alignment accuracy during missions?
-The team uses alignment mechanisms to align with the bases of missions for accuracy, which is crucial for the successful completion of tasks.
What is the process for designing a trip with the Laserbot?
-The process involves designing an attachment, programming it, testing it for errors, and repeating the process until the most efficient and reliable design is achieved.
Outlines
🤖 Evolution of Laserbot Design
The script introduces Laser Robotics and their journey in improving robot design over five years. Starting with a bulky and unbalanced robot based on a tutorial model, they progressively made modifications, leading to a compact, symmetric, and balanced robot design. The 13th version of the Laserbot 13 is highlighted for its stability, compactness, and symmetric design, featuring thin wheels, hidden wires, and efficient field navigation with two color sensors. The robot's efficiency is attributed to gravity-assisted attachments, easy motor space for power transfer, and instant gear locking mechanisms. The design philosophy emphasizes learning from previous iterations to enhance subsequent models, with a focus on reliability, efficiency, and practical performance.
🛠️ Robot Attachments and Programming Strategies
This paragraph delves into the design and improvement of robot attachments and programming strategies. The team at Laser Robotics uses passive mechanisms and 360-degree capabilities for their attachments, with gears and motors serving multiple functions. They employ linear motions for various missions and constantly refine their designs for enhanced reliability. The programming aspect focuses on the use of Spike Prime Python for more complex code, incorporating error correction functions and PID logic for smooth and accurate navigation. The script also discusses the importance of testing and debugging, with a methodical approach to evaluating robot performance through repeated tasks and recording success rates in an Excel file. The goal is to select the most practical and consistent hardware or software solutions based on these performance scores. The presentation concludes with a mention of leveraging line-following and reducing travel distance as part of their strategy for efficient robot operation.
Mindmap
Keywords
💡Robot Charging Session
💡Laserbot 13
💡Over-engineering
💡Attachments
💡Efficiency
💡PID Logic
💡Backlash
💡Passive Mechanisms
💡Line Following
💡Performance Score
Highlights
The Laser Robotics team aims to improve robot charging sessions through their presentation.
The Laserbot 13 design has evolved over five years, starting from a bulky and unbalanced model to a more refined version.
In the second year, the robot was more symmetric and balanced, but the port was over-engineered.
The third version of the robot was compact, allowed for easy attachments, and had hidden wires, winning first place in design awards.
The 11th version of the robot was taller with a higher center of gravity, winning the states in robot game and qualifier.
The 13th version of the robot has improved stability and a lower center of gravity, winning in qualifiers and states.
The robot's design is 17 by 18 square, with thin wheels and compact size for stability without sacrificing space.
The robot features two color sensors for better field navigation and six points of ground contact for stability.
Efficiency is achieved with gravity-assisted attachments and motor space optimization for power transfer.
Attachments are designed to utilize the 360-degree capabilities of the robot, with gears that lock into place instantly.
Passive mechanisms and linear motions are used in the design to solve missions with minimal motor usage.
Designs are constantly tested and improved for reliability and efficiency, with multiple versions of each attachment.
The team uses Spike Prime Python for programming, allowing for more complex code and error correction.
PID logic is implemented for smooth error correction in robot navigation.
The team has decoded the proportional, integral, derivative aspects of motor inconsistency for accurate navigation.
Performance is measured through a systematic evaluation, including success rates in various navigation tasks.
The team leverages line following and reduces travel distance to complete missions efficiently.
Passive mechanisms and one-way doors are utilized to complete multiple missions with minimal motor usage.
Alignment mechanisms are used for accurate mission interaction, ensuring precision in robot tasks.
The design process includes attachment, program, and error testing for reliability and efficiency.
Transcripts
hi we're the laser Robotics and today
we'll be helping you improve your robot
charging session we will be presenting
our robot presentation and along the way
be giving you some advice on how to
improve your drug suggestions
this is the design of the laserbot 13.
over the past five years we've improved
dramatically in our first year we were
just trying things out a robot was based
off a tutorial model that was not
marginalized it was tall bulky and was
not balanced this is our very first
version in our second year we were
progressing we had made modifications of
pocket design with a more symmetric and
balanced robot but we over engineered
the port this is our third version in
the third year we were great we a robot
was completely original extremely
Compact and allowed for easy drop down
attachments it also had hidden wires we
run first place in the robot and design
award in qualifiers and states in our
fourth year of clue of perfecting a
robot have relentlessly improved it was
tall at a higher center of gravity and
we won the states in robot game and
qualifier this is our 11th version this
year we are exceeding we have improved
stability we have lowered the center of
gravity we have a systematic evaluation
of our robot design and we won the
qualifier and states
this is our 13th version
with each iteration we learned from the
designs of inefficiencies of the last to
improve the next
our robot is a perfect 17 by 18 square
the wheels are as thin as possible and
it's also as compact as possible while
still maintaining stability it's durable
without sacrificing space no wires show
and it has a symmetric design we have
two color sensors for better field
navigation six points of ground contact
for stability flat sides and weight on
the back to help balance out attachments
a robot is very efficient for multiple
reasons some of these that are that are
attachments drop on using gravity and
they're secured by using upgraded facing
axles and for the launch area is really
easy because of our square shape and our
motor space up making it easier to
transfer power our gears also lock into
place instantly using upward facing
axles
as for our attachments we use as many
passive mechanisms as possible and we
create our attachments in a way that
utilize a 360 degree capabilities of the
robot we have gears that lock into place
and our Motors are used for multiple
things we also use a lot of linear
motions to solve missions
sometimes good designs have to be
sacrificed to further improve upon them
so new ideas are tested in multiple ways
attachments are constantly being
improved on to improve reliability and
efficiency and we also have countless
versions of every single attachment in
this picture you can see two different
designs of our second trip attachment
although many of the key features are
similar they're one of them is
completely redesigned for our
programming this year we use a spike
Prime python it's a better alternative
to block coding because it allows for
more complex code for our error
correction this year we have two main
air correction functions which may
include line falling and Gyro forward an
air correction system allows for easier
field navigation and accuracy use PID
logic to allow for maximum smoothness
all commonly used pieces of coat have a
dedicated function to keep the code as
clean as possible we had frequent
comments to make debugging easy over the
years we have truly decoded proportional
integral derivative all Motors are
inherently inconsistent because of
backlash which is an unavoidable issue
when the robot is driving the
inconsistency builds which leads to
inaccurate navigation PID is a universal
and flexible error correction logic
proportional means the bigger the
current air the bigger correction this
is the most commonly used and well
understood piece of code integral is the
bigger cumulative error the bigger
correction this can find drifts and
values and detect when the robot slowly
deviates away from its Target derivative
is the bigger change of error in the
bigger correction this will react to
sudden changes and outliers in data we
can fine-tune these PID parameters to
suit our needs
over the past five years we have learned
that our robot may look good but not
function efficiently so we were
important aspects of the robot
navigation 10 times each which may
include line falling turning Moving
Straight every time with or without
attachments and at different speed
levels record a password on an Excel
file we'd calculate that percentage of
success and use that percentage to sex
success as a performance score we use
this score to pick the most practical
and consistent option which should
either be Hardware or software
permission strategy this year we tried
to leverage line following as much as
possible and reduce travel distance
through this time in
completed five trips 15 missions in two
minutes and 30 seconds with a high score
we use a lot of packing mechanisms this
year which are mechanisms that preserve
as many Motors as possible and use the
motion of the robot to and gravity to
power missions we use these to complete
more than two missions in every trip we
also use a lot of one-way doors which
are a type of passive mechanism we use
one-way doors to lock onto objects or
missions without the use of motors and
we use this as an easy way to bring up
or drop-off units around the map for
alignment we use alignment mechanisms to
align with the basis of missions for
accuracy when we've been designing a
trip what we do is we design an
attachment program tends to try and
error and repeat
that's the end of our presentation
thanks for watching and stay tuned for
more like this
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