Hocki

Hocki
Year Of Creation	2020-2021
Versions
Current Version	1.0
Update Year	2020-2022
Wins/Losses	1/2
Information and Statistics
Weight Class	Hobby Weight
Weapon Class	(Translational Drift Spinner/Meltybrain)
Combined Wins/Losses	1/2
Weapon Speed	3600 RPM

Hocki is a Meltybrain, a combat robot that spins itself to attack. Unlike other robots, which have a stationary frame and spinning weapon, in this robot the entire frame is the weapon, and the robot spins itself to attack. This allows the robot to store more energy while spinning slower, which allows for hits to connect better. Such a design requires a control system which uses sensors to estimate the position of the robot. This robot utilizes custom circuitry and software to allow the frame to move, spin, and attack.

Competitions

Due to COVID-19 this robot did not go to competitions.

Design

(Hocki) V1.0

Team Lead: Valentin Richter

Team Mentor: Varun Madabushi

Members: John Bowzard, Kevin Xiao, Madeline Belew, Steven Zhao

Drive Motors	Scorpion HKIV-4020-860KV
Drive Motor Controllers	iFlight SucceX X80A
Receiver	FS-A8S
Remote Control	FS-i6X
Battery	2x Turnigy Graphene Panther 1200mAh 6S 75C Battery Pack w/XT60
(OTHER:)

Mechanical

Overall Design and Construction

The robot is comprised of an aluminum ring with aluminum top and bottom plates bolted on. All interior components (electronics, drive assembly) are sandwiched between the two rings.

One priority in the design is increasing the moment of inertia as much as possible by moving heavier components outwards. The main structure of the robot is the aluminum ring, which is CNC machined out of a single piece. This CNC machined part was ordered from Xometry due to obstacles in HAAS training and shop access due to the COVID-19 pandemic. After receiving the ring, it was tapped to accept screws which hold the top and bottom plates as well as the impactor tooth. The top and bottom plates were machined on the waterjet cutter and sanded to fit the grooves in the ring, as well as the motor and wheel mounts.

Another priority is keeping the center of mass centered at the midpoint of the wheels. If it were not, the kinematic center of rotation would be far from the dynamic center of rotation, resulting in drift and preventing the accelerometers from accurately measuring the centripetal acceleration. Thus care is taken in the placement of interior and exterior components to balance the robot.

We selected a 1-tooth design as the 1 tooth can cancel the weight of the motors in the back.

Drive

Describe structures/mechanisms here such as Drive, Ring, yada yada

Mounting

Drive train mounts screwed into both top and bottom plates and allow for assembly of wheel, motor, and pulley system.

Thermal pads used to adhere ESCs to bottom plate. Thin metal bar screwed to bottom plate above ESCs to improve stability and limit movement. PCB holder screwed into bottom and top plates. PCB is mounted onto 3D-printed PCB holder using 4 screws and rubber spacers.

Electronics

Control Board

The control board is mounted at the heart of the robot and connects to the LED, IR receiver, and ESC boards. On the control board, there are 4 accelerometers, 2 magnetometers, a 10 kHz bandpass filter, and a 20kHz bandpass filter. It also connects to a Teensy 4.1, which acts as a microcontroller and data logger. The bandpass filters are part of the IR Detector.

Due to electrical failures that could not be remedied during the chip shortage, the magnetometers and bandpass filters were not utilized for Motorama 2022. The design of 4 accelerometers is 3 more than typical translational drift robots have, which allows higher accuracy from the reduced sensor arsenal. During the competition, the first version of the board had to be used after shorts caused the regulator subsystems of the V2 boards to fail.

Key differences between the first and second versions of the control board are that the second version supports the complex LED board and that the accelerometers are not at a 45° angle to the board. The accelerometers, which are located around the estimated center of mass and rotation of the robot, would have been oversaturated at the 45° angle if the bot spun up to the theoretical RPM, which is not possible due to that calculation ignoring drag.

LED Board

Software

Controls and Data Logging

We derived equations to calculate rotational velocity from measured centripetal acceleration without needing to know the exact center of mass by using data from a pair x or y measurements from the accelerometers. With this method, we calculated four rotational velocities and averaged them to find the rotational velocity of the robot with minimized noise. We then integrated this velocity to get the angle the robot was oriented, setting zero to be the initial direction the robot was facing. However, even with this method we found that the position of the robot would drift at rest but was relatively accurate at higher rotational speeds.

To translate while spinning, we alternated pulsing the left and right motor speeds, each for half of a rotation, which is illustrated in the below image. However, during competition we were not able to translate in a controlled direction, rather translating in one random direction regardless of controller input.

We logged each axis of every accelerometer, as well as the average rotational velocity and the position of the robot at a frequency of 20 Hz. We stored this data in a .txt file on an SD card inserted onto the Teensy board. For the logging, we added 16 lines of data to a buffer before flushing the lines to the file.

See also

• Chonkii

Notes:

Rendition of us (hopefully) pucking up our opponents when we bounce back at them for the counterattack

Named after its resemblance to a hockey puck

Original Builders: Afshan Chandani, Varun Madabushi, Juan Elizondo, Hank Hellstrom, Darren Kosen, Nelson Jiang, Valentin Richter, Kevin Xiao, Sarkis Ter Maritorsyan, Keaton Sadoski, Alex Yu