The Generic Manipulation Driver Package - Implements a ROS Interface over the robotics toolbox for Python

Overview

Armer Driver

QUT Centre for Robotics Open Source License: MIT Build Status Language grade: Python Coverage

image

Armer documentation can be found here

image

Armer aims to provide an interface layer between the hardware drivers of a robotic arm giving the user control in several ways:

In addition to a multiple control method layer, Armer is designed to be a compatability layer allowing the user to use the same code across different robotic platforms. Armer supports control for physical and simulated arms giving users the ability to develop even without access to a physical manipulator.

Below is a gif of 3 different simulated arms moving with the same cartesian velocity commands.

image

Requirements

Several ROS action servers, topics and services are set up by Armer to enable this functionality. A summary of these can be found here.

Armer is built on the Python Robotics Toolbox (RTB) and requires a URDF loaded RTB model to calculate the required movement kinematics, RTB comes with browser based simulator Swift which Armer uses as an out of the box simulator.

Due to these supporting packages using Armer with a manipulator will require several requirements:

Software requirements

Robot specific requirements

  • ROS drivers with joint velocity controllers
  • Robotics Toolbox model

Installation

Copy and paste the following code snippet into a terminal to create a new catkin workspace and install Armer to it. Note this script will also add the workspace to be sourced every time a bash terminal is opened.

sudo apt install python3-pip 
mkdir -p ~/armer_ws/src && cd ~/armer_ws/src 
git clone https://github.com/qcr/armer.git && git clone https://github.com/qcr/armer_msgs 
cd .. && rosdep install --from-paths src --ignore-src -r -y 
catkin_make 
echo "source ~/armer_ws/devel/setup.bash" >> ~/.bashrc 
source ~/armer_ws/devel/setup.bash
echo "Installation complete!"

Supported Arms

Armer relies on the manipulator's ROS driver to communicate with the low level hardware so the the ROS drivers must be started along side Armer.

Currently Armer driver has packages that launches Armer and the target manipulator's drivers are bundled together. If your arm model has a hardware package, control should be a fairly plug and play experience. (An experience we are still working on so please let us know if it isn't.). Below are the github pages to arms with hardware packages. Install directions can be found on their respective pages.

For more information on setting up manipulators not listed here see the Armer documentation, Supported Arms.

Usage

The Armer interface can be launched with the following command:

roslaunch armer_{ROBOT_MODEL} robot_bringup.launch config:={PATH_TO_CONFIG_YAML_FILE} sim:={true/false}

After launching, an arm can be controlled in several ways. Some quick tutorials can be referenced below:

For more information and examples see the Armer documentation

Owner
QUT Centre for Robotics (QCR)
A collection of the open source projects released by the QUT Centre for Robotics (QCR).
QUT Centre for Robotics (QCR)
Denoising Diffusion Implicit Models

Denoising Diffusion Implicit Models (DDIM) Jiaming Song, Chenlin Meng and Stefano Ermon, Stanford Implements sampling from an implicit model that is t

465 Jan 05, 2023
you can add any codes in any language by creating its respective folder (if already not available).

HACKTOBERFEST-2021-WEB-DEV Beginner-Hacktoberfest Need Your first pr for hacktoberfest 2k21 ? come on in About This is repository of Responsive Portfo

Suman Sharma 8 Oct 17, 2022
TensorFlow2 Classification Model Zoo playing with TensorFlow2 on the CIFAR-10 dataset.

Training CIFAR-10 with TensorFlow2(TF2) TensorFlow2 Classification Model Zoo. I'm playing with TensorFlow2 on the CIFAR-10 dataset. Architectures LeNe

Chia-Hung Yuan 16 Sep 27, 2022
Churn prediction

Churn-prediction Churn-prediction Data preprocessing:: Label encoder is used to normalize the categorical variable Data Transformation:: For each data

1 Sep 28, 2022
Using deep learning model to detect breast cancer.

Breast-Cancer-Detection Breast cancer is the most frequent cancer among women, with around one in every 19 women at risk. The number of cases of breas

1 Feb 13, 2022
The code is an implementation of Feedback Convolutional Neural Network for Visual Localization and Segmentation.

Feedback Convolutional Neural Network for Visual Localization and Segmentation The code is an implementation of Feedback Convolutional Neural Network

19 Dec 04, 2022
Learning What and Where to Draw

###Learning What and Where to Draw Scott Reed, Zeynep Akata, Santosh Mohan, Samuel Tenka, Bernt Schiele, Honglak Lee This is the code for our NIPS 201

Scott Ellison Reed 337 Nov 18, 2022
[CoRL 21'] TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo

TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo Lukas Koestler1*    Nan Yang1,2*,†    Niclas Zeller2,3    Daniel Cremers1

TUM Computer Vision Group 744 Jan 04, 2023
Developing your First ML Workflow of the AWS Machine Learning Engineer Nanodegree Program

Exercises and project documentation for the 3. Developing your First ML Workflow of the AWS Machine Learning Engineer Nanodegree Program

Simona Mircheva 1 Jan 13, 2022
Generative Flow Networks for Discrete Probabilistic Modeling

Energy-based GFlowNets Code for Generative Flow Networks for Discrete Probabilistic Modeling by Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Vo

Narsil-Dinghuai Zhang 51 Dec 20, 2022
Predicting path with preference based on user demonstration using Maximum Entropy Deep Inverse Reinforcement Learning in a continuous environment

Preference-Planning-Deep-IRL Introduction Check my portfolio post Dependencies Gym stable-baselines3 PyTorch Usage Take Demonstration python3 record.

Tianyu Li 9 Oct 26, 2022
A python library for self-supervised learning on images.

Lightly is a computer vision framework for self-supervised learning. We, at Lightly, are passionate engineers who want to make deep learning more effi

Lightly 2k Jan 08, 2023
This repo contains the pytorch implementation for Dynamic Concept Learner (accepted by ICLR 2021).

DCL-PyTorch Pytorch implementation for the Dynamic Concept Learner (DCL). More details can be found at the project page. Framework Grounding Physical

Zhenfang Chen 31 Jan 06, 2023
Official repository of the paper Privacy-friendly Synthetic Data for the Development of Face Morphing Attack Detectors

SMDD-Synthetic-Face-Morphing-Attack-Detection-Development-dataset Official repository of the paper Privacy-friendly Synthetic Data for the Development

10 Dec 12, 2022
Telegram chatbot created with deep learning model (LSTM) and telebot library.

Telegram chatbot Telegram chatbot created with deep learning model (LSTM) and telebot library. Description This program will allow you to create very

1 Jan 04, 2022
Official code for: A Probabilistic Hard Attention Model For Sequentially Observed Scenes

"A Probabilistic Hard Attention Model For Sequentially Observed Scenes" Authors: Samrudhdhi Rangrej, James Clark Accepted to: BMVC'21 A recurrent atte

5 Nov 19, 2022
SysWhispers Shellcode Loader

Shhhloader Shhhloader is a SysWhispers Shellcode Loader that is currently a Work in Progress. It takes raw shellcode as input and compiles a C++ stub

icyguider 630 Jan 03, 2023
Distance correlation and related E-statistics in Python

dcor dcor: distance correlation and related E-statistics in Python. E-statistics are functions of distances between statistical observations in metric

Carlos Ramos Carreño 108 Dec 27, 2022
A collection of easy-to-use, ready-to-use, interesting deep neural network models

Interesting and reproducible research works should be conserved. This repository wraps a collection of deep neural network models into a simple and un

Aria Ghora Prabono 16 Jun 16, 2022
Official code for "Mean Shift for Self-Supervised Learning"

MSF Official code for "Mean Shift for Self-Supervised Learning" Requirements Python = 3.7.6 PyTorch = 1.4 torchvision = 0.5.0 faiss-gpu = 1.6.1 In

UMBC Vision 44 Nov 21, 2022