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Full-Text Articles in Computer Engineering

Reasoning From Point Clouds, Joey Wilson Dec 2019

Reasoning From Point Clouds, Joey Wilson

Computer Engineering

Over the past two years, 3D object detection has been a major area of focus across industry and academia. This is primarily due to the difficulty of learning data from point clouds. While camera images are fixed size and can therefore be easily trained on using convolution, point clouds are unstructured series of points in three dimensions. Therefore, there is no fixed number of features, or a structure to run convolution on. Instead, researchers have developed many ways of attempting to learn from this data, however there is no clear consensus on what is the best method, as each has …


Weight Controlled Electric Skateboard, Zachary Barram, Carson Bertozzi, Vishnu Dodballapur Jun 2019

Weight Controlled Electric Skateboard, Zachary Barram, Carson Bertozzi, Vishnu Dodballapur

Computer Engineering

Technology and the way that humans interact is becoming more vital and omnipresent with every passing day. However, human interface device designers suffer from the increasingly popular “designed for me or people like me” syndrome. This design philosophy inherently limits accessibility and usability of technology to those like the designer. This places severe limits of usability to those who are not fully able as well as leaves non-traditional human interface devices unexplored. This project set out to explore a previously uncharted human interface device, on an electric skateboard, and compare it send user experience with industry leading human interface devices.


Labeling Paths With Convolutional Neural Networks, Sean Wallace, Kyle Wuerch Jun 2019

Labeling Paths With Convolutional Neural Networks, Sean Wallace, Kyle Wuerch

Computer Engineering

With the increasing development of autonomous vehicles, being able to detect driveable paths in arbitrary environments has become a prevalent problem in multiple industries. This project explores a technique which utilizes a discretized output map that is used to color an image based on the confidence that each block is a driveable path. This was done using a generalized convolutional neural network that was trained on a set of 3000 images taken from the perspective of a robot along with matching masks marking which portion of the image was a driveable path. The techniques used allowed for a labeling accuracy …


The Soul Annoyed Robot: A Senior Project Report, Dayton Andrew Muxlow, Christian Johansen Jun 2019

The Soul Annoyed Robot: A Senior Project Report, Dayton Andrew Muxlow, Christian Johansen

Computer Engineering

Our goal for this senior project was to create a competitive robot designed to com- pete in Roborodentia 2019. Our project started during the Winter 2019 quarter, and ended with the competition on May 18, 2019. During that time, we developed an accurate solenoid shooting mechanism, an elevated conveyor belt to carry poker chips, and a servo arm to scoop in stacks of poker chips. These hardware compo- nents were attached to a circular differential-drive wooden base designed to be easy to control. We also planned out our match strategy and implemented this strategy with software written in C/Wiring to …


Planr.: Planar Learning Autonomous Navigation Robot, Gabrielle S. Santamorena, Daniel Kasman, Jesus Mercado, Ben Klave, Andrew Weisman, Anthony Fortner Jun 2019

Planr.: Planar Learning Autonomous Navigation Robot, Gabrielle S. Santamorena, Daniel Kasman, Jesus Mercado, Ben Klave, Andrew Weisman, Anthony Fortner

Computer Engineering

PLANR is a self-contained robot capable of mapping a space and generating 2D floor plans of a building while identifying objects of interest. It runs Robot Operating System (ROS) and houses four main hardware components. An Arduino Mega board handles the navigation, while an NVIDIA Jetson TX2, holds most of the processing power and runs ROS. An Orbbec Astra Pro stereoscopic camera is used for recognition of doors, windows and outlets and the RPLiDAR A3 laser scanner is able to give depth for wall detection and dimension measurements. The robot is intended to operate autonomously and without constant human monitoring …