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Human Dynamics Estimation (HDE) is a collection of YARP modules for the estimation of the dynamics in humans while physically interacting with a robot.
- Rationale
- Overview
- How to use it
- Dependencies
- How to install
- Documentation
- Citing this work
- Acknowledgments
HDE is the on-line evolution of the Matlab code present in MAPest repository. The general idea is to be able in real-time to estimate the forces acting on the human body during a physical interaction with a robot. A ROS-based visualizer allows to visualize in real-time this interaction.
The best way to use this repository is to exploit all the available suggested tools that allow you to have the real-time forces and motion estimation.
For reproducing the same experimental set-up as in figure, you would need the following dependencies:
- the iCub robot
- the Rviz visualizer
If you are using them, you don't have to modify this code. Clearly, they are not dependencies in terms of software but in terms of tools for which the code is tailored. If you want to use another visualizer or another robot, keep in mind that the code requires minor modifications.
A general overview of HDE is described as follows:
- a human-state-provider module;
- a human-forces-provider module;
- a human-dynamics-estimator module;
- the human-viz-bridge module for the visualization.
What about the raw data?
The data about the human kinematics are provided to the human-state-provider module by the YARP interface yarp::dev::IFrameProvider. Here there is the implementation of the YARP driver for acquiring data if the motion capture is obtained through a Xsens MVN system.
The data related to the external forces are provided to the human-forces-provider module whether the forces are coming from a YARP port (e.g.,in the case of the robot wrenches) or in the form of a AnalogSensor -by using the yarp::dev::IAnalogSensor interface- when they are coming from a force-torque device (see here the implementation of YARP Device Drivers for various commercial Six Axis Force Torque sensors).
The human model is a URDF model with its non standard extension (see here for more details).
Here following there is a list of dependencies you need for using this repository. It is worth to notice that the build ones and the libraries are mandatory to install your project. Instead, the optional dependencies are defined optional in the sense that the project is built even if they are not included. The installation of the all dependencies is strongly suggested if you want to have a visual feedback of how much your estimation is good.
For installing the dependencies you can decide to install them individually or to use the robotology-superbuild with the ROBOTOLOGY_ENABLE_DYNAMICS option that automatically is in charge of installing all the dependencies you need (except for the optional ones). Keep in mind that the robotology-superbuild is surely the fastest way to install them but it contains many more things than you need!
- CMake: an open-source, cross-platform family of tools designed to build, test and package software.
- YCM: a CMake project whose only goal is to download and build several other projects.
- YARP: a library and toolkit for communication and device interfaces.
- iDynTree: a library of robots dynamics algorithms for control, estimation and simulation.
- Eigen: a C++ template library for linear algebra.
- IPOPT: a software package for large-scale nonlinear optimization for the inverse kinematics code in the human-state-provider module.
- ROS: an open-source provider of libraries and tools for creating robot applications. More details for the installation here.
Finally, after having installed the dependencies, you can install the HDE project:
git clone https://github.com/robotology-playground/human-dynamics-estimation.git
mkdir build
cd buildcmake -DCMAKE_INSTALL_PREFIX=/path/to/your/installation/folder -G "name-of-your-cmake-generator" ..where the name-of-your-cmake-generator is your project generator, see Cmake-Generators. For example, on macOS you may choose Xcode, or on Unix Unix Makefiles.
Then, for compiling
cmake --build . --config Release
and installing
cmake --build . --config Release --target install
The documentation for HDE is automatically extracted from the C++ code using Doxygen, and it is available here .
Please cite the following publication if you are using the code contained in this repository for your own research and/or experiments
The CoDyCo Project achievements and beyond: Towards Human Aware Whole-body Controllers for Physical Human Robot Interaction
Francesco Romano, Gabriele Nava, Morteza Azad, Jernej Camernik, Stefano Dafarra, Oriane Dermy, Claudia Latella, Maria Lazzaroni, Ryan Lober, Marta Lorenzini, Daniele Pucci, Olivier Sigaud, Silvio Traversaro, Jan Babic, Serena Ivaldi, Michael Mistry, Vincent Padois, Francesco Nori
IEEE Robotics and Automation Letters
DOI: 10.1109/LRA.2017.2768126
http://ieeexplore.ieee.org/document/8093992
The bibtex code for including this citation is provided:
@article{romano2017codyco,
title={The CoDyCo Project achievements and beyond: Towards Human Aware Whole-body Controllers for Physical Human Robot Interaction},
author={Romano, Francesco and Nava, Gabriele and Azad, Morteza and Camernik, Jernej and Dafarra, Stefano and Dermy, Oriane and Latella, Claudia and Lazzaroni, Maria and Lober, Ryan and Lorenzini, Marta and others},
year={2017},
DOI={10.1109/LRA.2017.2768126},
publisher={IEEE},
journal={IEEE Robotics and Automation Letters},
url={http://ieeexplore.ieee.org/document/8093992},
}
The development of HDE is supported by the FP7 EU projects CoDyCo (No. 600716 ICT 2011.2.1 Cognitive Systems and Robotics) and by H2020 EU projects An.Dy (No. 731540 H2020-ICT-2016-1). The development is also supported by the Istituto Italiano di Tecnologia.