Project

# Title Team Members TA Documents Sponsor
36 Anti-Lock Braking for Bicycles
Aidan Rodgers
Ethan Chastain
Leon Ku
Nithin Balaji Shanthini Praveena Purushothaman design_document4.pdf
final_paper2.pdf
other1.jpeg
photo1.jpeg
presentation1.pptx
proposal2.pdf
video
Anti-Lock Braking for Bicycles

Team Members:
- Ethan Chastain (ecc5)
- Aidan Rodgers (aidanfr2)
- Leon Ku (leonku2)

# Problem

Bicycles present a challenge because they often lack or charge a premium for the features that cars have, like Anti-Lock Braking Systems (ABS). This happens because bicycles are primarily designed for short distance commuting. Unlike cars that come with a range of amenities, bicycles prioritize simplicity. However, this difference in design leads to a discrepancy in safety and convenience features. Bicycle riders do not have the braking capabilities and automated speed regulation that many cars offer. This absence of features like ABS can be particularly dangerous as bicycles are prone to skidding; thus increasing the risk of accidents. As mobility solutions, bicycles sacrifice these functionalities, which means riders must navigate roads with heightened awareness and limited technological assistance.

# Solution

In order to improve the safety of bicycles via cheaper, preventative features, we could consider adding technologies commonly used in cars. For instance, adding an Anti-lock Braking System (ABS) would reduce the risk of skidding by braking more efficiently; thereby improving overall safety. More importantly, the use of ABS ensures better stability for riders and helps prevent accidents like collisions at an intersection. By embracing these technologies, bicycles can offer riders safer, cheaper rides with improved ease of use. We plan to use one of the bikes provided by the workshop and add a braking system that both detects locking and modulates braking to account for it.

# Solution Components

## Subsystem 1 - Speed sensing

We plan to use a Hall effect sensor (potential part number: DRV5023BIQLPGMQ1) to sense rotational motion of the bicycle’s rear wheel, to determine the speed of the bicycle. This will interface directly with the microcontroller to allow for the braking system to pulse the brakes if locking occurs. The sensor will also be used to record data, in order to test for proper operation.

## Subsystem 2 - Braking

This system takes inputs from the microprocessor to operate the brakes of the bicycle. The braking subsystem consists of a servo motor and a gear system to mechanically pull the brake cable, upon input from the microprocessor. As this system will interfere with the normal mechanical braking system of the bicycle, we will implement buttons in place of the typical brake controls on the handlebars, which will interface with the microprocessor to allow for the bicycle to brake.

## Subsystem 3 - Microprocessor

The microprocessor subsystem will take information from the Hall effect sensors about the rotational speed of the bicycle’s wheel. This subsystem will use an ATMega controller to implement the control algorithms. We plan to use LQR or PID control as a means of tracking constant slopes to prevent wheel locking when decelerating. By this method, we will be able to flash a controller onto the microcontroller in order to embed our control on the PCB.

# Criterion For Success

To qualitatively test the bicycle’s anti-lock braking mechanism, we will place the bicycle on a treadmill and slam the brakes, to observe visually the bicycle’s braking operation. During this test, data from the Hall effect sensor relating to the speed of the bicycle’s rear wheel will be recorded during the test, demonstrating that the bicycle is slowing down properly and efficiently.


VoxBox Robo-Drummer

Craig Bost, Nicholas Dulin, Drake Proffitt

VoxBox Robo-Drummer

Featured Project

Our group proposes to create robot drummer which would respond to human voice "beatboxing" input, via conventional dynamic microphone, and translate the input into the corresponding drum hit performance. For example, if the human user issues a bass-kick voice sound, the robot will recognize it and strike the bass drum; and likewise for the hi-hat/snare and clap. Our design will minimally cover 3 different drum hit types (bass hit, snare hit, clap hit), and respond with minimal latency.

This would involve amplifying the analog signal (as dynamic mics drive fairly low gain signals), which would be sampled by a dsPIC33F DSP/MCU (or comparable chipset), and processed for trigger event recognition. This entails applying Short-Time Fourier Transform analysis to provide spectral content data to our event detection algorithm (i.e. recognizing the "control" signal from the human user). The MCU functionality of the dsPIC33F would be used for relaying the trigger commands to the actuator circuits controlling the robot.

The robot in question would be small; about the size of ventriloquist dummy. The "drum set" would be scaled accordingly (think pots and pans, like a child would play with). Actuators would likely be based on solenoids, as opposed to motors.

Beyond these minimal capabilities, we would add analog prefiltering of the input audio signal, and amplification of the drum hits, as bonus features if the development and implementation process goes better than expected.

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