MAPest (Maximun-A-Posteriori estimation) is a probabilistic tool for estimating dynamics variables in humans.
The code in this repository works only off-line and to solve the problem of the estimation of human dynamics you need to have a dataset of different measurements coming from sensors. For the moment the repository consists of two type of experiments:
- 1st experiment (2dofBowingTask): where we consider a very simplified human model with 3 link and 2 Dofs and a sensor architecture composed by the Vicon motion capture + an IMU + one forceplate;
- 2nd experiment (23links_human): where the model is composed by 23 links and for the sensor structure by the Xsens suit + two sensorized shoes.
Detailes on the experiments in the README of each related Section.
Please cite the following publications if you are using the code contained in this repository for your own research and/or experiments:
Latella, C.; Traversaro, S.; Ferigo, D.; Tirupachuri, Y.; Rapetti, L.;
Andrade Chavez, F.J.; Nori, F.; Pucci, D. Simultaneous Floating-Base
Estimation of Human Kinematics and Joint Torques. Sensors 2019, 19, 2794
doi: https://doi.org/10.3390/s19122794
https://www.mdpi.com/1424-8220/19/12/2794
and
Latella, C. Human Whole-Body Dynamics Estimation for Enhancing Physical Human-Robot Interaction