Aplica\c{c}\~ao de ros como ferramenta de ensino a rob\'otica / using ros as a robotics teaching tool

• URL: http://arxiv.org/abs/2203.16923v1
• Date: Thu, 31 Mar 2022 09:48:21 GMT
• Title: Aplica\c{c}\~ao de ros como ferramenta de ensino a rob\'otica / using ros as a robotics teaching tool
• Authors: Daniel Maia Evangelista, Pedro Benevides Cavalcante, Afonso Henriques Fontes Neto Segundo
• Abstract summary: The study of robotic manipulators is the main goal of Industrial Robotics Class. This article aims to expose the use of the Robot Operation System (ROS) as a tool to develop a robotic arm.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: The study of robotic manipulators is the main goal of Industrial Robotics Class, part of Control Engineers training course. There is a difficulty in preparing academic practices and projects in the area of robotics due to the high cost of specific educational equipment. The practical classes and the development of projects are very important for engineers training, it is proposed to use simulation software in order to provide practical experience for the students of the discipline. In this context, the present article aims to expose the use of the Robot Operation System (ROS) as a tool to develop a robotic arm and implement the functionality of forward and inverse kinematics. Such development could be used as an educational tool to increase the interest and learning of students in the robotics discipline and to expand research areas for the discipline.

Related papers

• RAMPA: Robotic Augmented Reality for Machine Programming and Automation [4.963604518596734]
  This paper introduces Robotic Augmented Reality for Machine Programming (RAMPA) RAMPA is a system that utilizes the capabilities of state-of-the-art and commercially available AR headsets, e.g., Meta Quest 3. Our approach enables in-situ data recording, visualization, and fine-tuning of skill demonstrations directly within the user's physical environment.
  arXiv  Detail & Related papers  (2024-10-17T10:21:28Z)
• RoboScript: Code Generation for Free-Form Manipulation Tasks across Real and Simulation [77.41969287400977]
  This paper presents textbfRobotScript, a platform for a deployable robot manipulation pipeline powered by code generation. We also present a benchmark for a code generation benchmark for robot manipulation tasks in free-form natural language. We demonstrate the adaptability of our code generation framework across multiple robot embodiments, including the Franka and UR5 robot arms.
  arXiv  Detail & Related papers  (2024-02-22T15:12:00Z)
• Software Engineering for Robotics: Future Research Directions; Report from the 2023 Workshop on Software Engineering for Robotics [0.0]
  Software Engineering for Robotics was held in Detroit, Michigan in October 2023. The goal of the workshop was to bring together thought leaders across robotics and software engineering to coalesce a community. This report serves to summarize the motivation, activities, and findings of that workshop.
  arXiv  Detail & Related papers  (2024-01-22T19:21:44Z)
• Toward General-Purpose Robots via Foundation Models: A Survey and Meta-Analysis [82.59451639072073]
  General-purpose robots operate seamlessly in any environment, with any object, and utilize various skills to complete diverse tasks. As a community, we have been constraining most robotic systems by designing them for specific tasks, training them on specific datasets, and deploying them within specific environments. Motivated by the impressive open-set performance and content generation capabilities of web-scale, large-capacity pre-trained models, we devote this survey to exploring how foundation models can be applied to general-purpose robotics.
  arXiv  Detail & Related papers  (2023-12-14T10:02:55Z)
• RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation [68.70755196744533]
  RoboGen is a generative robotic agent that automatically learns diverse robotic skills at scale via generative simulation. Our work attempts to extract the extensive and versatile knowledge embedded in large-scale models and transfer them to the field of robotics.
  arXiv  Detail & Related papers  (2023-11-02T17:59:21Z)
• WIP: Development of a Student-Centered Personalized Learning Framework to Advance Undergraduate Robotics Education [3.4359491310368786]
  The study of robotics at the college level represents a wide range of interests, experiences, and aims. This paper presents a work-in-progress on a learn-ing system that will provide robotics students with a personalized learning environment.
  arXiv  Detail & Related papers  (2023-09-10T20:00:25Z)
• Active Predicting Coding: Brain-Inspired Reinforcement Learning for Sparse Reward Robotic Control Problems [79.07468367923619]
  We propose a backpropagation-free approach to robotic control through the neuro-cognitive computational framework of neural generative coding (NGC) We design an agent built completely from powerful predictive coding/processing circuits that facilitate dynamic, online learning from sparse rewards. We show that our proposed ActPC agent performs well in the face of sparse (extrinsic) reward signals and is competitive with or outperforms several powerful backprop-based RL approaches.
  arXiv  Detail & Related papers  (2022-09-19T16:49:32Z)
• Tiny Robot Learning: Challenges and Directions for Machine Learning in Resource-Constrained Robots [57.27442333662654]
  Machine learning (ML) has become a pervasive tool across computing systems. Tiny robot learning is the deployment of ML on resource-constrained low-cost autonomous robots. Tiny robot learning is subject to challenges from size, weight, area, and power (SWAP) constraints. This paper gives a brief survey of the tiny robot learning space, elaborates on key challenges, and proposes promising opportunities for future work in ML system design.
  arXiv  Detail & Related papers  (2022-05-11T19:36:15Z)
• Applying PBL in the Development and Modeling of kinematics for Robotic Manipulators with Interdisciplinarity between Computer-Assisted Project, Robotics, and Microcontrollers [0.0]
  This article proposes the application of Project Based Learning (ABP) through the design, development, mathematical modeling of a robotic manipulator. It is an integrative project of the disciplines of Industrial Robotics, Microcontrollers and Computer Assisted Design with students of the Control and Automation Engineering of the University of Fortaleza.
  arXiv  Detail & Related papers  (2022-03-31T10:01:24Z)
• HeRo 2.0: A Low-Cost Robot for Swarm Robotics Research [2.133433192530999]
  This paper presents the design of a novel platform for swarm robotics applications that is low cost, easy to assemble using off-the-shelf components, and deeply integrated with the most used robotic framework: ROS (Robot Operating System) The robotic platform is entirely open, composed of a 3D printed body and open-source software. Results demonstrate that the proposed mobile robot is very effective given its small size and reduced cost, being suitable for swarm robotics research and education.
  arXiv  Detail & Related papers  (2022-02-24T22:23:14Z)
• From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence [113.06484656032978]
  Article argues that embodied intelligence is a key driver for the advancement of machine learning technology. We highlight challenges and opportunities specific to embodied intelligence. We propose research directions which may significantly advance the state-of-the-art in robot learning.
  arXiv  Detail & Related papers  (2021-10-28T16:04:01Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.