Project

# Title Team Members TA Documents Sponsor
40 Remote Area Clearance Device (RACE)
Bjorn Oberg
Rahul Sachdeva
Nicholas Ratajczyk appendix
final_paper
presentation
proposal
People drop small items such as earrings, needles etc. These can sometimes be hard to find for the naked eye, or can be in a hard to reach position. We want to build upon the ECE 110 project, and build a car that can detect metal, and pick the object up. The car will have an autonomous mode and a manual mode. In the manual mode, it will be controlled remotely by the user, through Bluetooth protocol. This car, with the metal detection circuit, has additional applications outside the home as well. It can be used as a low cost alternative to look for landmines in war torn regions. Despite the United States having the world’s largest army, IEDs and mines still pose significant difficulties for the Army with regard to engineering operations and maneuver support. A department of defense lab as shown a strong interest in this project and have offered to provide support to our team in the form of robots, processors, sensors, etc.
They have offered to allow us to use one of their “mini-bots” which we may use instead of the ECE 110 car.

We will use the chassis and the motor drivers from the ECE 110 class. We will build a metal detection circuit, and the detecting coil will be mounted in front of the car, facing downwards. When metal is detected, the car will take a step back, and use TTL logic to swipe the possible area with a small vacuum to pick up the object. We will use TTL chips to implement navigation logic, and integrate Bluetooth so that the car can receive and send signals. We will build the software that will allow the user to move the car using a laptop, and control the vacuum.

In the autonomous mode, the car will be able to navigate itself (only in a fixed, chosen room). We will fill prior information such as the dimensions of the room, and the location of the door of the ECE 445 lab. There will be a fixed base position of the car, and we will have Bluetooth beacons around the room to act as markers for recalibrating the position. The car will be equipped with wheel encoders, compass, and accelerometers. We want to give the user the ability to pick a spot where he has dropped an object (such as desk 5), and the car will go there from the base and look for the metal object near that desk.

Our base goal is to implement the metal detection circuit along with the manual operation mode of the car. Our reach goal is to implement the autonomous mode of operation.

VoxBox Robo-Drummer

Craig Bost, Nicholas Dulin, Drake Proffitt

VoxBox Robo-Drummer

Featured Project

Our group proposes to create robot drummer which would respond to human voice "beatboxing" input, via conventional dynamic microphone, and translate the input into the corresponding drum hit performance. For example, if the human user issues a bass-kick voice sound, the robot will recognize it and strike the bass drum; and likewise for the hi-hat/snare and clap. Our design will minimally cover 3 different drum hit types (bass hit, snare hit, clap hit), and respond with minimal latency.

This would involve amplifying the analog signal (as dynamic mics drive fairly low gain signals), which would be sampled by a dsPIC33F DSP/MCU (or comparable chipset), and processed for trigger event recognition. This entails applying Short-Time Fourier Transform analysis to provide spectral content data to our event detection algorithm (i.e. recognizing the "control" signal from the human user). The MCU functionality of the dsPIC33F would be used for relaying the trigger commands to the actuator circuits controlling the robot.

The robot in question would be small; about the size of ventriloquist dummy. The "drum set" would be scaled accordingly (think pots and pans, like a child would play with). Actuators would likely be based on solenoids, as opposed to motors.

Beyond these minimal capabilities, we would add analog prefiltering of the input audio signal, and amplification of the drum hits, as bonus features if the development and implementation process goes better than expected.

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