Project

# Title Team Members TA Documents Sponsor
37 Automated Casino Assistant - Odds Booster
Jack Arndt
Marco Rojas
Tim Green
uma Lath design_document1.pdf
final_paper1.pdf
photo2.jpg
presentation1.pptx
proposal1.pdf
# Automated Casino Assistant

Team Members:

Marco Rojas (marcor2)

Jack Arndt (jrarndt2)

Timothy Green (trgreen2)

# Problem

Before heading to the casino, individuals need to assess how much money they are willing to lose, since as the saying goes, “The house always wins”. Or do they? Is there potentially a way to bring the casino games to the comfort of your home and train/optimize your strategies to ask a different question, “How much money should I win?”

# Solution

The Automated Casino Assistant (or Odds Booster for a more marketable name) is a kit designed to help players learn and manage casino games such as Blackjack or Texas Hold’em. The kit involves a central communicable device along with a custom deck of cards which will be used to determine the best possible move for each player along with the outcome of each hand of the game. This device is an innovation as it brings both the ease and simplicity as well as the ability to learn the game that can be provided by a virtual game into the superior enjoyment and atmosphere of a physical game. Digital poker tables that provide a similar experience exist but cost thousands of dollars. Our design achieves this functionality without an expensive custom table and while allowing for physical cards and chips.

# Subsystem 1

The first aspect of the device is the card reading ability. Each card in the deck will have a thin RFID tag on it. An RFID tag reader will be used to determine which cards are in play at which time. By selecting a game and the number of players, the assistant will know which card is going to which player after being swiped and dealt and will keep track of each player’s hand. We will be looking to create our own deck of cards that will perform at casino quality, while being able to be scanned and communicated to the central display screen. There are other possible ways to indicate the cards being played on the table, such as a light sensor or movement detector. For the time being, an RFID tag and scanner system is the desirable option.

# Subsystem 2

The assistant will have a central display to instruct the group on what to do next in the game as well as determining the winner at the end of each hand. During a hand, the assistant will be able to suggest a move to the player using statistical analysis and the information available to the player. This display will be able to detect the cards on the table using the communication system set up with the custom deck, crunch the numbers to give optimized options, and give the results to users in a sensible fashion. We can either make our own device that can handle this, or simply make it an app on the App Store (which would only require the purchase of the custom deck/scanner if we went this route).

# Further Possibilities

There are other games that don’t require the use of cards, such as games with dice (craps) or wheel (roulette). These can also be implemented in our design potentially if the interest is there. The likely outcomes and payouts of these games are just as important as the card games, just with less variability than cards.

# Criterion For Success

Assuming just the usage of cards, to successfully complete this project, we will need a reliable way to know which cards are being played on the table. Once that is set up, a wireless communication network needs to set in place for the cards on the table to be sent to our device that will be able to reliably and correctly give optimal decisions and give these readings to the user. This will need to be stress tested tirelessly and need clear and concise communication to the users in order to make this work. There are certainly more things that can be added to make this project more complex, this is simply the baseline idea of what we would like to accomplish.

Web Board Discussion URL: https://courses.engr.illinois.edu/ece445/pace/view-topic.asp?id=70130

Decentralized Systems for Ground & Arial Vehicles (DSGAV)

Mingda Ma, Alvin Sun, Jialiang Zhang

Featured Project

# Team Members

* Yixiao Sun (yixiaos3)

* Mingda Ma (mingdam2)

* Jialiang Zhang (jz23)

# Problem Statement

Autonomous delivery over drone networks has become one of the new trends which can save a tremendous amount of labor. However, it is very difficult to scale things up due to the inefficiency of multi-rotors collaboration especially when they are carrying payload. In order to actually have it deployed in big cities, we could take advantage of the large ground vehicle network which already exists with rideshare companies like Uber and Lyft. The roof of an automobile has plenty of spaces to hold regular size packages with magnets, and the drone network can then optimize for flight time and efficiency while factoring in ground vehicle plans. While dramatically increasing delivery coverage and efficiency, such strategy raises a challenging problem of drone docking onto moving ground vehicles.

# Solution

We aim at tackling a particular component of this project given the scope and time limitation. We will implement a decentralized multi-agent control system that involves synchronizing a ground vehicle and a drone when in close proximity. Assumptions such as knowledge of vehicle states will be made, as this project is aiming towards a proof of concepts of a core challenge to this project. However, as we progress, we aim at lifting as many of those assumptions as possible. The infrastructure of the lab, drone and ground vehicle will be provided by our kind sponsor Professor Naira Hovakimyan. When the drone approaches the target and starts to have visuals on the ground vehicle, it will automatically send a docking request through an RF module. The RF receiver on the vehicle will then automatically turn on its assistant devices such as specific LED light patterns which aids motion synchronization between ground and areo vehicles. The ground vehicle will also periodically send out locally planned paths to the drone for it to predict the ground vehicle’s trajectory a couple of seconds into the future. This prediction can help the drone to stay within close proximity to the ground vehicle by optimizing with a reference trajectory.

### The hardware components include:

Provided by Research Platforms

* A drone

* A ground vehicle

* A camera

Developed by our team

* An LED based docking indicator

* RF communication modules (xbee)

* Onboard compute and communication microprocessor (STM32F4)

* Standalone power source for RF module and processor

# Required Circuit Design

We will integrate the power source, RF communication module and the LED tracking assistant together with our microcontroller within our PCB. The circuit will also automatically trigger the tracking assistant to facilitate its further operations. This special circuit is designed particularly to demonstrate the ability for the drone to precisely track and dock onto the ground vehicle.

# Criterion for Success -- Stages

1. When the ground vehicle is moving slowly in a straight line, the drone can autonomously take off from an arbitrary location and end up following it within close proximity.

2. Drones remains in close proximity when the ground vehicle is slowly turning (or navigating arbitrarily in slow speed)

3. Drone can dock autonomously onto the ground vehicle that is moving slowly in straight line

4. Drone can dock autonomously onto the ground vehicle that is slowly turning

5. Increase the speed of the ground vehicle and successfully perform tracking and / or docking

6. Drone can pick up packages while flying synchronously to the ground vehicle

We consider project completion on stage 3. The stages after that are considered advanced features depending on actual progress.

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