Project

# Title Team Members TA Documents Sponsor
2 Antweight Battlebot
Gauthami Yenne
Jingyu Kang
Nandika Vuyyuri
Haocheng Bill Yang design_document1.pdf
final_paper1.pdf
grading_sheet1.pdf
photo1.jpg
photo2.jpg
presentation1.pdf
proposal1.pdf
proposal2.pdf
video
# Antweight Battlebot
Nandika Vuyyuri (vuyyuri2) \
Gauthami Yenne (gyenne2) \
Jingyu Kang (jingyuk2)

# Problem
The goal of this project is to create an antweight battlebot that would weigh less than 2 lbs in order to participate in the Antweight Battlebot Competition. The criteria given are that all robots must have clearly visible and controlled mobility; must be controlled via either Bluetooth or WIFI using a microcontroller with an manual operation for disconnection; and rotational blade which would contact the arena 5 inches above the ground level and could come to a complete stop within 60 seconds.

# Solution
The battlebot will be mounted with a tombstone attacking mechanism in order to disable the opponent’s vehicle.

# Solution Components
## Power System:
We need a max of 16V considering the motor we are using for moving our robot around so we plan to use Thunder Power 325 mAh 3s battery (THP 325-3SR70J) which is 35g and is the lightest battery we could find that met our requirements. Other battery options weighted about 65g to 105g which would be too heavy to meet the criteria since the weight limit for the entire battlebot should be about 900g. \
Another option is to use flat lithium batteries since the weight of the batteries are significantly lighter than the regular batteries. However, the problem of this would be that the power would not be sufficient enough for the battlebot to move and perform the tasks required as most of the lithium batteries cannot produce significant power at a single instant but rather is a long lasting battery.

## MCU:
The ESP32-C3 (ESP32-C3-DevKitM-1), which is known for its low power consumption, will be used for connection between the battlebot and the controller utilizing its built-in Wifi and Bluetooth system. We will use Arduino IDE in order to program the ESP32-C3 to control the robot. We will use this to control the robot’s mobility and attacking mechanism. \n We have access to debugging and flashing tools that are compatible with the ESP32-C3 MCU.

## Attacking mechanism:
We plan to use the Emax RS2205 2600KV motor which is 30g. This motor has a fast RPM and is often used for drones actually which we are hoping will be a powerful attacking mechanism.

## Robot mobility
To maneuver the battlebot we will use a dual H-bridge configuration using the DRV8833 motor driver paired with high-torque Pololu Micro Metal Gear Motors and integrate the parts with the ESP32-C3-DevKitM-1.


## Materials
We plan to use a mixture of lightweight PET-G, ABS, and PLA+ materials. The primary reason for this choice is since they are more durable and flexible as well as heat-resistant which would be ideal for the nature of battlebots. Furthermore, considering majority of the parts would be created through 3D-printing, we assume that ABS or PEEK filament, which is primarily used for 3D-printers, would be ideal.


# Criterion For Success
Our High-level goal is to maneuver the robot away from the opponent with precision and control. Another goal is to have a horizontal spinning attacking mechanism which is ‘powerful’ enough to knock out robots of other shapes should not just ‘flick’ the other robot but actually make a significant impact to disable the opponent’s robot.

Backpack Buddy - Wearable Proximity/Incident Detection for Nighttime Safety

Jeric Cuasay, Emily Grob, Rahul Kajjam

Backpack Buddy - Wearable Proximity/Incident Detection for Nighttime Safety

Featured Project

# Backpack Buddy

Team Members:

- Student 1 (cuasay2)

- Student 2 (rkajjam2)

- Student 3 (eegrob2)

# Problem

The UIUC campus is relatively a safe place. We have emergency buttons throughout campus and security personnel available regularly. However, crime still occurs and affects students walking alone, especially at night. Staying up late at night working in a classroom or other building can lead to a long scary walk home. Especially when the weather is colder, the streets are generally less populated and walking home at night can feel more dangerous due to the isolation.

# Solution

A wearable system that uses night vision camera sensor and machine learning/intelligence image processing techniques to detect pedestrians approaching the user at an abnormal speed or angle that may be out of sight. The system would vibrate to alert them to look around and check their surroundings.

# Solution Components

## Subsystem 1 - Processing

Processing

Broadcom BCM2711 SoC with a 64-bit quad-core ARM Cortex-A72 processor or potentially an internal microprocessor such as the LPC15xx series for image processing and voltage step-down to various sensors and actuators

## Subsystem 2 - Power

Power

Converts external battery power to required voltage demands of on-system chips

## Subsystem 3 - Sensors

Sensors

Camera - Night Vision Camera Adjustable-Focus Module 5MP OV5647 to detect objects in the dark

Proximity sensor - detects obstacle distance before turning camera on, potentially ultrasonic or passive infrared sensors such as the HC-SR04

Haptic feedback - Vibrating Mini Motor Disc [ADA1201] to alert user something was identified

# Criterion For Success

The Backpack Buddy will provide an image based solution for identifying any imposing figure within the user's blind spots to help ensure the safety of our user. Our solution is unique as there currently no wearable visual monitoring solutions for night-time safety.

potential stuff:

Potentially: GNSS for location tracking, light sensor for outdoors identification, and heartbeat for user stress levels

camera stabilization

heat camera

Project Videos