Project
| # | Title | Team Members | TA | Documents | Sponsor |
|---|---|---|---|---|---|
| 36 | Personal Carrier Robot |
Alex Tanthiptham Deniz Caglar Okan Kocabalkanli |
Raman Singh | design_document1.pdf final_paper1.pdf other2.jpg other1.mp4 photo1.jpg photo2.PNG photo3.png photo4.png photo5.jpg proposal3.pdf proposal1.pdf proposal2.pdf video1.mp4 |
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| Team Members: - Okan Kocabalkanli (okan2) - Deniz Caglar (dcaglar2) - Jirawatchara Tanthiptham (jt20) # Problem In our current society, there are individuals who may lack the ability to carry objects by themselves. An example of this is elderly individuals who may be unable to carry heavy groceries. # Solution We can create a path-finding robot that will follow the individual while avoiding obstacles. We are planning on implementing this using ultrasonic depth imaging to detect obstacles. A series of rotating ultrasonic sensors will be imaging the surroundings of the robot. The person of interest will be sending GPS data to the robot through Bluetooth and another GPS chip will be present on the robot. The robot will calculate the distance between itself and the person of interest using the GPS data, and move in the correct direction based on the heading provided by an onboard compass chip. Combining the obstacle and goal direction data, we will employ a path-finding/SLAM algorithm to direct and move the robot through the terrain. # Solution Components ## Mechanical This subsystem will encompass the frame for mounting other components as well as the propulsion system of the unit. The system will be rear-wheel driven with each wheel powered by separate motors to allow for differential steering. ### Components: - Wooden chassis - A tank drive system with 4 wheels - 2 DC motors ## Power Management This subsystem will be powering the rest of the circuit including the PCB and the motors. ### Components: - A LiPo battery - LiPo battery charging circuit ## PCB This subsystem is the sensor suite and brain of our system, performing simultaneous localization and mapping (SLAM) and pathfinding for the system. This system will be generating a PWM signal for the stepper motor. The stepper motor then rotates the Radar Imaging sensors to generate a full field of view. From measured ultrasonic sensor data, obstacles in the systems environment are mapped. The subsystem uses this mapping in addition to data received from the RPI subsystem via SPI for path finding. When the user is in line-of-sight, MCU will be using the distance data from the RPI subsystem camera. When the user is out of line-of-sight, MCU will be using the user's gyroscope and accelerometer data from the RPI subsystem. Using either RPI data, the location of the user is set as the target point with Kalman Filter being used to predict these mapped points' trajectories. Using this trajectory information, the subsystem will create a probability grid. This grid will consist of specific size blocks with each having a collision probability. Using a path finding algorithm like A*, we draw a path between blocks to the target point in order to find the safest and shortest path. The system will compute the path from this and control the DC motors accordingly. ### Components: - A microcontroller - DC Motor controller - Step Motor Controller (TB67S128FTG) - Radar Imaging System Connector - Programmer Circuit - SPI Connection circuit to RPI - Simultaneous localization and mapping (SLAM) Algorithm - Kalman filter for Obstacle tracking and prediction - Roadmap/Grid path planning with A* ## RPI This subsystem obtains and processes the data necessary for simultaneous localization and mapping (SLAM) using a Raspberry Pi. By using a camera, the robot will detect a fixed-size tag. The fixed size will allow us to detect the distance using the camera perspective.This distance will be pass to the MCU over SPI. In case of a person blocks the camera view, we will switch to a "search mode" where the RPI will forward the phone's heading information (accelerometer, gyroscope ) to the MCU, which then will head the same heading as the user while avoiding obstacles until we find our user with our camera. ### Components: - Raspberry Pi - Bluetooth connection - RPI Camera ## User This is the subsystem that will directly interact with our users. In this subsystem, we will use a mobile app in order to send user’s GPS data over Bluetooth. For prototyping, we are planning on using an app called “Blynk”, which lets user transfer sensor data from a smartphone via Bluetooth. ### Components: - Smartphone # Criterion For Success - The robot should be able to consistently follow the phone holder through flat terrain with solid, straightforward obstacles. - The person of interest can be 3-10 meters away from the robot. - The obstacles should have a height of at least 30 cm over ground level. - The robot should also be able to carry a load of 3 kg over level ground. [Discussion thread]( https://courses.engr.illinois.edu/ece445/pace/view-topic.asp?id=72004) |
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