SMART Lab at Purdue University's repositories
ros-tutorial-gazebo-simulation
ROS tutorial by Purdue SMART lab: Gazebo simulation - autonomous mobile robot navigation and creating custom robots and sensor plugins
robust-control-tutorial
Robust control tutorial by Purdue SMART Lab: Sliding Mode Control (SMC) with MATLAB/Simulink example implementation
SMARTmBOT
The goal of this repository is to introduce a new, customizable, scalable, and fully opensource mobile robot platform, called SMARTmBOT. This repository provides a guide, and all design files and source codes so that you can build your own SMARTmBOT. SMARTmBOT can be useful for studying the basics of robotics, especially mobile robotics. It can also be used to study advanced topics such as swarm robotics.
SAN-NaviSTAR
This repository contains the source code for our paper: "NaviSTAR: Socially Aware Robot Navigation with Hybrid Spatio-Temporal Graph Transformer and Preference Learning". For more details, please refer to our project website at https://sites.google.com/view/san-navistar.
robotarium-rendezvous-RSSDOA
This repository contains the Matlab source codes (to use in Robotarium platform) of various rendezvous controllers for consensus control in a multi-agent / multi-robot system.
ros-tutorial-voice
This tutorial briefly covers how to control a robot over voice command. The user can control the robot using voice command and the robot acknowledges back to the user through a text-to-speech system, after executing the control action. E.g. Once the user ask the robot to "forward". The robot executes it and then sends a message over voice to the user saying the the "Requested action executed".
ros2-foxy-wearable-biosensors
This repository is a new wearable biosensors package for ROS2-Foxy. The ultimate goal of this repo is to expand the biosensors ecosystem in the Human-Robot Interaction (HRI) field. The package currently supports six wearable biosensors that can be used in HRI researches without behavioral constraints caused by limited hardware specifications (e.g., wired devices). We will keep updating this GitHub to support various wearable sensors on ROS 2 system. If you are interested in this project, please contact us.
ros-tutorial-robot-control-vision
ROS tutorial on iRobot Create2 robot control and CV based object detection by Purdue SMART lab
Harmful-Algae-Removal-USV
Oceans 2019 - Development of an Unmanned Surface Vehicle for Harmful Algae Remova
Attack_Detection-Sim
This repository contains the Matlab source codes of attack detection algorithm for multi-agent / multi-robot systems. The ROS Gazebo simulation using CAT Vehicle Testbed was modified to demonstrate the attack detection scenario on CAT vehicles at urban environments.
SeLRoS
Code repository for Semantic Layering in Room Segmentation via LLMs (SeLRoS). This repository includes 2D Map generation code and Room Information Interpreter code, and a data set containing ground truth, object information file, top view image, and room segmentation results for each environment for an experiment in 30 environments.
smart_mbot_ws
The goal of this repository is to share a ROS2 workspace for the SMARTmBOT. If you want to know more details about the SMARTmBOT, please visit our official GitHub page; https://github.com/SMARTlab-Purdue/SMARTmBOT
multirobot-consensus-robotarium
This repository consists of Robotarium implementations of various multi-robot consensus algorithms from the literature.
Sediment-Core-Sampler
The goal of this repository is to introduce a robotic underwater sediment sampling system based on the unmanned surface vehicle (USV) and underwater sediment sampler (USS) to collect bed sediment samples. This repository provides the detailed cost breakdown along with the source code and CAD files of the USS and the operational instructions.
SMART-TeleLoad
This repo is a practical stimulus tool for teleoperated human-robot teams. The tool is comprised of a customizable graphical user interface and subjective questionnaires to measure affective loads. We validated that this tool can invoke different levels of affective loads through extensive user experiments.