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a_star_non_holonomous_robot

Implementation of Astar algorithm in python for Non-holonomous Turtlebot-2 robot.

ackermann_steering_controller

advanced-lane-detection-using-hough-lines

Lane detection using Hough Lines and Perspective Transformation

ariac-agile_robotics_for_industrial_automation_competition_iteration1

ARIAC - Agile Robotics for Industrial Automation Competition. This package can pick up parts from the ARIAC industrial environment which are faulty and with the wrong pose(flipping)

ariac-agile_robotics_for_industrial_automation_competition_iteration_2

Agile Robotics Development in an industrial setup. In this particular scenario, there are faulty parts, faulty gripper as well as priority orders.

ariac-agile_robotics_for_industrial_automation_competition_iteration_3

Agile Robotics Development for ARIAC challenge hosted by NIST. Picking and delivering parts in an industrial environment with faulty parts/faulty gripper/sensor blackout/moving obstacles

astar_algorithm_rigid_robot

A_Star algorithm for a Rigid robot with 5 connected space freedom.

astar_turtlebot_ros_gazebo

Implementation of A star path planning algorithm in python and Simulated it on a Turtlebot 2 robot using ROS Gazebo

baxter-gazebo-simulation

ENPM661-Project4-Planning for Autonomous Robots

beginner_tutorials

A simple tutorial to create a package with a subscriber and publisher node using C++

buoy_detection_gaussian_mixture_model_em

competition_robot_modeling_and_planning

Competition_Robot_Modeling_and_Planning

convolutional-neural-networks---kaggle-dogs-vs-cats

Data classification is the process of sorting and organizing data into categories so that it is easier for us to retrieve and use this data anytime in the future. As per our problem statement, we are required to classify the given data as dogs and cats. This classification is to be performed using Convolution Neural Networks. Convolution network is a type of artificial neural network which uses the concept of perceptrons for supervised learning to analyze data. A convolution layer has an input layer, output layer, and some hidden layers which consists of convolution layers that uses a mathematical model to pass on the results to successive layers. In the given data set, we have 12500 testing data and 25000 training data that consists of dogs and cats. The training data is labeled and follows the format of dog/cat.0.jpg whereas testing data is unlabeled and the format is 0.jpg and so on.

cpp_hacker_rank

depth_first_search

dijkstra_implementation_point_and_rigid_robot

dummy

eight_puzzle_python

enpm661_projects

enpm673_perception_for_autonomous_robots

examples

Examples for class and other items

final_competition_ariac_agile_robotics_for_industrial_automation_competition

flickr_scraper

Simple Flickr Image Scraper

learnopencv

Learn OpenCV : C++ and Python Examples

line-fitting_ls_tls_ransac

lqr_lqg_kalmannobserver

lucas_kanade_tracker-opencv-python-

Implementation of Lucas Kanade Tracker using Opencv-Python

manikamakam.github.io

Build a Jekyll blog in minutes, without touching the command line.

modelling_baxter_robot_matlab_vrep

path_planning_depthfirstsearch_cpp14

Done as part of the course work - Introduction to Robot Programming