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ai_project_find_route

First the program will build a map/web of the cities first then preforms a BFS, where it doesn't keep track of the visted cities, to find shortest path.

algobowl

CSCI406 Project2: The algorithm determines a minimal length sequence of addition operations starting with 1 that computes all values in X.

c06a-git-and-stove

csc341_labs

collection of labs done in Computer Organization

csci261_labs

collection of labs done in programming concepts

csci262_labs

collection of labs done in Data Structures

csci262_pojects

collection of projects done in Data Structures

csci437_labs

Computer Vision Labs

custom_clue_game

Uses a custom Clue board and has the user go against 3 other bots, the player will use a interactive window to play the game. JAR file is available if you want to play; code is in src

dead_reckoning_open_loop_control

MEGN441 Lab2: Enables a robot capable of navigating a pre-planned course using open-loop control, look at memo for more details

design_showcase

MEGN441 Lab5: Done through Arduino and assumes the code is uploaded to a bot with two motors/wheels, draws shapes when given a pen

drawing_an_m_with_ros_turtles

CSCI473 Project1: Spawns a ROS Turtle bot that draws the letter M from the Colorado School of Mines logo

dynamic_programming_timber_verification

CSCI406 Project3: Given an array of n positive integers representing the length of segments that a tree will be split into, what is the maximum length of wood that you can leave the sawmill with if you can only take one segment at a time from the end of the log, alternating picks with a neighbor who is your intellectual equal

linux

maze_verification

CSCI406 Project4: Takes a maze input (like Grandpa Transit Map) and models the maze as a graph, then uses an BFS algorithm to solve the maze

music-note-detection

Islolates notes/symbol on a music sheet for machine learning

pong_game

Simple pong game made in C++ using SFML Library

reinforcement-learning-for-robot-wall-following

Start up a Gazebo simulation and runs a maze map, a robot will use Q-Learning to follow the walls of the maze through the use of lidar sensors, and will build a Q-Table from its trials in order to follow the walls

reinforcement_learning_for_robot_wall_following_problem_formulation

CSCI473 Project2 D2: Inside a Gaezbo 3D world the program will use ROS to allow a robot to follow walls through lidar sensors and a built in Q-Table

robot_navigation_through_maze_closed_loop_control

MEGN441 lab3: robot of navigating a given maze in closed loop control, look into memo for more details

robot_understanding_of_human_behavior_representation_construction

CSCI473 Project3 D1: Takes skeleton pose data and organizes them into histograms that will be used in machine learnig

robot_understanding_of_human_behavior_robot_learning_from_data

CSCI473 Project3 D2: Takes data that was organized from D1 and further organize it through the use of SVM and Kernel in order to be used in machine learning

solving-the-maze

Lab 4 for MEGN 441: extension of Lab 3 Maze traversal, but instead of providing the robot with prior information, the robot is expected to use sensing (IR sensor in the front and a ultrasonic sensor on its left) to explore the maze using wall following, and then optimally reduce its exploration traversal to find the best path through the maze.

tsp_timing_project

CSCI406 Project1: Travelling salesman problem solved through two ways: Exhaustive and Heuristric