Project for the Intelligent Robotics course at the university of Padua 2023-2024
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Updated
Feb 16, 2024 - HTML
Project for the Intelligent Robotics course at the university of Padua 2023-2024
Tiago Robot - Unity
Assignment of Software Architecture regarding the implementation of a software for TIAGo robot capable of recognizing an object and grasp it
This is the official Github repo of the GravaStars team of University of West Attica, for the remote participation in the Second SciRoc Challenge 2021, Episode 1, E01: Coffee Shop. This work was awarded with the second place in the SciRoc Challenge 2021 competition.
Code and data for the paper "When Do People Want an Explanation?", presented at HRI'24
CNR (National Research Council of Italy) internship project on timeline-based planning, using ROS (rospy) and the TIAGo robot on the Gazebo simulator.
Assistive Gym, a physics-based simulation framework for physical human-robot interaction and robotic assistance. The repository provides an extension of the framework that includes the integration of the TIAGo robot and the addition of new simulation environments. - Federico Pivotto, UniPD BSc Thesis
Reports and papers of different project completed
ROS-based project for Robot Control and Simulation course at Warsaw University of Technology.
Projects developed for the Intelligent Robotics course @ UniPD
Navigate in the environment, recognize objects using AprilTags, pick and place objects, recognize obstacles using laser and camera (project for Intelligent Robotics)
Final Project for the Course ENPM808X Software Development for Robotics
ROS2 and Navigation2 integration of TIAGo robot running in Webots simulator
ROS software architecture to perform some basic control on the PAL Robotics TIAGo robot through vocal commands.
Pick and Place with TIAGO Robot in ROS - 2023 - University of Padua
TIAGo Steel's implementation of a dual controller (in pose and effort) for the robotic arm.
Navigation in ROS2 with Nav2 introduced a lot of new features and possibilities. The goal of this assignment is to explore and test the new feature of navigating in a known environment while avoiding user-defined “keep out areas”.
In this project we proposed a tracking control strategy for a tracked mobile robot under longitudinal slip condition. The proposed control strategy is based on the dynamic model of the tracked robot, in which the longitudinal slip of the left and right tracks are described by two unknown parameters.
This is a meta package grouping necessary components to manage physical resources of the Tiago robot.
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