Project :: ECE 445 - Senior Design Laboratory

#	Title	Team Members	TA	Documents	Sponsor
43	FPS Game Somatosensory Enhancement Gun Controller	Beining Chen Haochen Zhang Peilin He	Yixuan Wang	design_document1.pdf final_paper2.pdf photo1.jpg photo2.jpg proposal1.pdf video
	# FPS Game Somatosensory Enhancement Gun Controller ## Team Members: - Peilin He (peilinh2) - Beining Chen (Beining4) - Haochen Zhang (Hz39) # Problem The functions of video game controllers nowadays are very limited to the gaming machine, and are mostly in the form of joy-stick or controller. Playing shooting games on PC with a mouse or joystick can lower a gamer's gaming experience and make gaming a less realistic experience.. Especially when VR games slowly occupy the video game market,a non-traditional controller, or a somatosensory enhancement gun-shaped controller is necessary. # Solution The solution is to introduce the use of Somatosensory Enhancement accessories. A Somatosensory Enhancement shooting controller can make shooting video games more realistic and interactive. We plan to build a gun-shaped shooting controller that could simulate target aiming, gun recoil, reload bullets, and potentially flash bomb and smoke bomb. # Solution Components ## Subsystem 1: Processor We will use a PIC32 microcontroller to handle memory allocation for the cache. It can also communicate with the Wifi chip to transfer data. https://www.mouser.com/new/microchip/microchip_pic32/ ## Subsystem 2: Wireless connection First of all, our design regarding a gun-model video game controller is not only limited to video games. It could also accomplish the function of a mouse which could control the cursor. Therefore, a wireless connection such as bluetooth is needed. ### Wireless Connection parts: ESP32-PICO-D4 Espressif Systems ESP32 PICO module. https://www.gridconnect.com/products/esp32-pico-d4-espressif-systems-esp32-pico-module?variant=9740028510244&utm_term=&utm_campaign=Shopping+-+Desktop&utm_source=adwords&utm_medium=ppc&hsa_acc=7986939350&hsa_cam=18566303751&hsa_grp=147887861968&hsa_ad=627525968785&hsa_src=g&hsa_tgt=pla-2078855464952&hsa_kw=&hsa_mt=&hsa_net=adwords&hsa_ver=3&gclid=Cj0KCQiAw8OeBhCeARIsAGxWtUwmVoJj798qb5FMj6avdIXGO-ydMxWrTO9nwvRTR41JAaAWuykQRAQaAodcEALw_wcB DROK 12V Audio Receiver Blue~Tooth Module DC 5V-12V Portable Wire~Less Electronics Stereo Music Receive Circuit Chip https://www.amazon.com/Bluetooth-DROK-Receiver-Electronics-Headphone/dp/B07P94Z9XR/ref=sr_1_5?crid=25GB25DVFXH3E&keywords=bluetooth%2Bchip&qid=1674762910&sprefix=bluetooth%2Bchip%2B%2Caps%2C365&sr=8-5&th=1 ## Subsystem 3: Motion detection Motion detector Use gyroscope somatosensory to control the computer cursor. HiLetgo GY-521 MPU-6050 https://www.amazon.com/HiLetgo-MPU-6050-Accelerometer-Gyroscope-Converter/dp/B01DK83ZYQ/ref=sr_1_3?keywords=Gyroscope%2BSensor&qid=1674763585&sr=8-3&th=1 ## Subsystem 4: Vibration Vibrator to simulate gun recoil. We can use a motor vibration part to achieve this. We will be using a 308-100 8mm vibration motor to mount on our PCB. https://www.precisionmicrodrives.com/ab-006 ## Subsystem 5: Power This subsystem will supply power to the rest of the sub-system. It contains a battery and a USB charger. If available batteries can not provide enough power, we will choose to use external power supplies. # Criterion For Success Our solution should be easily accessible from any computer with bluetooth. Our gun controller should function as a cursor that accurately reflects the aiming point on the screen.In FPS video games, physically turning the aiming point left and right will turn the player's angle of view left and right with according degree. During a game, pulling the trigger on the gun controller will give the player physical shaking action to simulate gun recoil. Also, pulling the bolt will complete a bullet reload in the game. # Anticipated Difficulties Our anticipated difficulties revolve around connecting bluetooth from our device to a PC which can accurately reflect real time cursor position and functions similar to a mouse. Precisely connecting the gun controller with motion detector and gravity sensor to calculate screen coordinate to reflect cursor position is expected to take a long time implementing and debugging. Final Presentation slides: https://docs.google.com/presentation/d/1qrRwniksCi8U4OrzGqL8e-9CaAXRSu2n/edit?usp=sharing&ouid=115941454030265620199&rtpof=true&sd=true

Featured Project

# Oxygen Delivery Robot

Team Members:

- Rutvik Sayankar (rutviks2)

- Aidan Dunican (dunican2)

- Nazar Kalyniouk (nazark2)

# Problem

Children's interstitial and diffuse lung disease (ChILD) is a collection of diseases or disorders. These diseases cause a thickening of the interstitium (the tissue that extends throughout the lungs) due to scarring, inflammation, or fluid buildup. This eventually affects a patient’s ability to breathe and distribute enough oxygen to the blood.

Numerous children experience the impact of this situation, requiring supplemental oxygen for their daily activities. It hampers the mobility and freedom of young infants, diminishing their growth and confidence. Moreover, parents face an increased burden, not only caring for their child but also having to be directly involved in managing the oxygen tank as their child moves around.

# Solution

Given the absence of relevant solutions in the current market, our project aims to ease the challenges faced by parents and provide the freedom for young children to explore their surroundings. As a proof of concept for an affordable solution, we propose a three-wheeled omnidirectional mobile robot capable of supporting filled oxygen tanks in the size range of M-2 to M-9, weighing 1 - 6kg (2.2 - 13.2 lbs) respectively (when full). Due to time constraints in the class and the objective to demonstrate the feasibility of a low-cost device, we plan to construct a robot at a ~50% scale of the proposed solution. Consequently, our robot will handle simulated weights/tanks with weights ranging from 0.5 - 3 kg (1.1 - 6.6 lbs).

The robot will have a three-wheeled omni-wheel drive train, incorporating two localization subsystems to ensure redundancy and enhance child safety. The first subsystem focuses on the drivetrain and chassis of the robot, while the second subsystem utilizes ultra-wideband (UWB) transceivers for triangulating the child's location relative to the robot in indoor environments. As for the final subsystem, we intend to use a camera connected to a Raspberry Pi and leverage OpenCV to improve directional accuracy in tracking the child.

As part of the design, we intend to create a PCB in the form of a Raspberry Pi hat, facilitating convenient access to information generated by our computer vision system. The PCB will incorporate essential components for motor control, with an STM microcontroller serving as the project's central processing unit. This microcontroller will manage the drivetrain, analyze UWB localization data, and execute corresponding actions based on the information obtained.

# Solution Components

## Subsystem 1: Drivetrain and Chassis

This subsystem encompasses the drive train for the 3 omni-wheel robot, featuring the use of 3 H-Bridges (L298N - each IC has two H-bridges therefore we plan to incorporate all the hardware such that we may switch to a 4 omni-wheel based drive train if need be) and 3 AndyMark 245 RPM 12V Gearmotors equipped with 2 Channel Encoders. The microcontroller will control the H-bridges. The 3 omni-wheel drive system facilitates zero-degree turning, simplifying the robot's design and reducing costs by minimizing the number of wheels. An omni-wheel is characterized by outer rollers that spin freely about axes in the plane of the wheel, enabling sideways sliding while the wheel propels forward or backward without slip. Alongside the drivetrain, the chassis will incorporate 3 HC-SR04 Ultrasonic sensors (or three bumper-style limit switches - like a Roomba), providing a redundant system to detect potential obstacles in the robot's path.

## Subsystem 2: UWB Localization

This subsystem suggests implementing a module based on the DW1000 Ultra-Wideband (UWB) transceiver IC, similar to the technology found in Apple AirTags. We opt for UWB over Bluetooth due to its significantly superior accuracy, attributed to UWB's precise distance-based approach using time-of-flight (ToF) rather than meer signal strength as in Bluetooth.

This project will require three transceiver ICs, with two acting as "anchors" fixed on the robot. The distance to the third transceiver (referred to as the "tag") will always be calculated relative to the anchors. With the transceivers we are currently considering, at full transmit power, they have to be at least 18" apart to report the range. At minimum power, they work when they are at least 10 inches. For the "tag," we plan to create a compact PCB containing the transceiver, a small coin battery, and other essential components to ensure proper transceiver operation. This device can be attached to a child's shirt using Velcro.

## Subsystem 3: Computer Vision

This subsystem involves using the OpenCV library on a Raspberry Pi equipped with a camera. By employing pre-trained models, we aim to enhance the reliability and directional accuracy of tracking a young child. The plan is to perform all camera-related processing on the Raspberry Pi and subsequently translate the information into a directional command for the robot if necessary. Given that most common STM chips feature I2C buses, we plan to communicate between the Raspberry Pi and our microcontroller through this bus.

## Division of Work:

Given that we already have a 3 omni wheel robot, it is a little bit smaller than our 50% scale but it allows us to immediately begin work on UWB localization and computer vision until a new iteration can be made. Simultaneously, we'll reconfigure the drive train to ensure compatibility with the additional systems we plan to implement, and the ability to move the desired weight. To streamline the process, we'll allocate specific tasks to individual group members – one focusing on UWB, another on Computer Vision, and the third on the drivetrain. This division of work will allow parallel progress on the different aspects of the project.

# Criterion For Success

Omni-wheel drivetrain that can drive in a specified direction.

Close-range object detection system working (can detect objects inside the path of travel).

UWB Localization down to an accuracy of < 1m.

## Current considerations

We are currently in discussion with Greg at the machine shop about switching to a four-wheeled omni-wheel drivetrain due to the increased weight capacity and integrity of the chassis. To address the safety concerns of this particular project, we are planning to implement the following safety measures:

- Limit robot max speed to <5 MPH

- Using Empty Tanks/ simulated weights. At NO point ever will we be working with compressed oxygen. Our goal is just to prove that we can build a robot that can follow a small human.

- We are planning to work extensively to design the base of the robot to be bottom-heavy & wide to prevent the tipping hazard.