Mock Presentation

Description

Like the mock design review and the mock demo, the mock presentation is an informal, mandatory event designed to better prepare you for your Final Presentation. These sessions are run by staff and students from the Department of Communication, who are experts in teaching professional communication skills. In this session, you are only given five minutes to present a few slides on one major component of your project. Your presentation should include at least one block diagram, one graph/plot, and some math. You will also have the opportunity to see several other mock presentations. You will be given feedback based on the organization of the presentation, delivery and your ability to present as a team (so all members must speak).

Requirements and Grading

The mock presentation is meant to be a small subset of your final presentation. It is recommended that you choose some aspect of your project (like a major block from your block diagram) and present the design, requirements, and verification for that block. In order to get relevant feedback on your presentation skills, your mock presentation should also have an introduction (where the project is introduced) and a conclusion that wraps everything up. You will receive feedback on both your delivery, the format of your slides, and the organization of your presentation.

Your slides should generally include:

  1. Title slide: Names, group #, title.
  2. Introduction slide: What is the project?
  3. Objective slide: What problem does this solve?
  4. Design Slides: A few slides on design, requirements and verification (should include block diagram, math, graphs, figures, tables).
  5. Conclusion: Wrap things up, future work.

Mock presentation is graded credit/no credit based on attendance and apparent effort; showing up completely unprepared will earn no credit. An example mock presentation can be found here: example mock presentation

Submission and Deadlines

Sign-up is handled through PACE. Time slots are 1 hour long, and multiple groups will share a time slot. This will give you an opportunity to give and receive feedback from your peers. You will be required to stay until all groups have presented and received feedback.

High Noon Sheriff Robot

Yilue Pan, Shuting Shao, Yuan Xu, Youcheng Zhang

Featured Project

# MEMBERS:

- Yuan Xu [yuanxu4]

- Shuting Shao [shao27]

- Youcheng Zhang [yz64]

- Yilue Pan [Yilvep2]

# TITLE:

HIGH NOON SHERIFF ROBOT

PROBLEM:

Nowadays with the increasing number of armed attacks and shooting incidents. The update for public places needs to be put on the agenda. Obviously, we could not let police and security to do all the jobs since humans might neglect some small action of threat behind hundreds of people and could not respond quickly to the threat. A second of hesitation might cost an innocent life. Our team aims on making some changes to this situation since nothing is higher than saving lifes not only victims but also gunners. We find some ideas in the Old western movies when two cowboys are going to a high noon duel, the sheriff will pull out the revolver quicker than the other and try to warn him before everything is too late. If we can develop a robot that can detect potential threats and pull out weapons first in order to warn the criminal to abandon the crime or use non-lethal weapons to take him down if he continues to pull out his gun.

# SOLUTION OVERVIEW:

In order to achieve effective protection in a legal way, we have developed the idea of a security robot. The robot can quickly detect dangerous people and fire a gun equipped with non-lethal ammunition to stop dangerous events.

The robot should satisfy the following behavioral logic:

- When the dangerous person is acting normally and there is no indication of impending danger, the robot should remain in standby mode with its robot arm away from the gun.

- When the dangerous person is in a position ready to draw his gun or other indication of dangerous behavior, the robot is also in a drawn position and its arm is already clutching the gun.

- When the dangerous person touches his gun, The robot should immediately draw the gun, move the hammer and finish aiming and firing to control the dangerous person. This type of robot would need to include three subsystems: Detection system, Electrical Control system, and Mechanical system.

# SOLUTION COMPONENTS:

## [SUBSYSTEM #1: DETECTION SUBSYSTEM]

This subsystem consists of a camera and PC. We are going to use YOLO v5 to detect object, determine the position of human and the gun. Use DeepSORT to track the object, let the camera follow the opponent. Use SlowFast to detect opponent’s behavior.

## [SUBSYSTEM #2: ELECTRICAL CONTROL SYSTEM]

This subsystem consists of a STM32, two high speed motors, two gimbal motors, one motor for revolver action and position sensor. The STM32 serves as the controller for the motors. The high speed motor will be used to move the mechanical grab to grab the revolver and pull it out as fast as possible so that it will use the position sensor as the end stop point instead of PID control. The gimbal motors serve as Yaw and Pitch motion for the revolver to control the accuracy of the revolver so that it needs encoders to give the angle feedback.

## [SUBSYSTEM #3: MECHANICAL SYSTEM]

This subsystem consists of a three-degree-of-freedom robot arm and a clamping mechanism fixed to the end of the arm. The clamping mechanism is used to achieve the gripping of the gun, the moving of the hammer and the pulling of the trigger. The mechanical arm is used to lift and aim the gun.

# CRITERION FOR SUCCESS

- Move Fast. The robot must draw its gun and aim faster than the opponent；

- Warning First. If opponent’s hand moves close to the gun on his waist, the robot should draw the gun and aim it at the opponent without firing. If the opponent gives up drawing a gun and surrender, the robot should put its gun back in place. Otherwise, the robot will shoot at the opponent.

- Accurate shooting. Under the premise that the opponent may move, the robot must accurately shoot the opponent's torso.

# DISTRIBUTION OF WORK

- EE Student Shuting Shao: Responsible for object detection and object tracking.

- EE Student Yuan Xu: Responsible for behavior detection and video processing.

- EE Student Youcheng Zhang: Responsible for electrical control system.

- ME Student Yilue Pan: Responsible for the Mechanical system.