Published February 23, 2018 | Version v1

Learning by Demonstration for Motion Planning of Upper-Limb Exoskeletons

  • 1. Unit of Biomedical Robotics and Biomicrosystems, Department of Engineering, Università Campus Bio-Medico, Rome, Italy
  • 2. The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
  • 3. Biomedical Neuroengineering Research Group, Miguel Hernandez University, Elche, Spain
  • 4. Departamento de Ingeniería en Automática, Electrónica, Arquitectura y Redes de Computadores, Universidad de Cádiz, Cádiz, Spain
  • 5. GLIC—Italian Network of Assistive Technology Centers, Bologna, Italy
  • 6. Unit of Physical and Rehabilitation Medicine, Università Campus Bio-Medico, Rome, Italy
  • 7. The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy; Fondazione Don Carlo Gnocchi, Firenze, Italy

Description

Raw data acquired necessary to perform the algorithm introduced in this paper.

a) CA_task1.xlsx 
In this file the mean value of robot joint angles computed on the data acquired during the task1 performing with different object positions and used to carry out the CA-sim in Fig.11 are reported (in radians) for the DMP control, IK inverse jacobian and IK with swivel angle.

b) CA_task2.xlsx 
In this file the mean value of robot joint angles computed on the data acquired during the task2 performing with different object positions and used to carry out the CA-sim in Fig.11 are reported (in radians) for the DMP control, IK inverse jacobian and IK with swivel angle.                

c) CA_task3.xlsx 
In this file the mean value of robot joint angles computed on the data acquired during the task3 performing with different object positions and used to carry out the CA-sim in Fig.11 are reported (in radians) for the DMP control, IK inverse jacobian and IK with swivel angle.                

d) GCA_sim_task1.xlsx 
In this file the mean value of robot joint angles computed on the data acquired during the task1 performing with different object positions and used to carry out the GCA-sim in Tab.2 are reported (in radians) for 25 different anthropometry        

e) GCA_sim_task2.xlsx 
In this file the mean value of robot joint angles computed on the data acquired during the task2 performing with different object positions and used to carry out the GCA-sim in Tab.2 are reported (in radians) for 25 different anthropometry        

f) GCA_sim_task3.xlsx 
In this file the mean value of robot joint angles computed on the data acquired during the task3 performing with different object positions and used to carry out the GCA-sim in Tab.2 are reported (in radians) for 25 different anthropometry            

g) GCA_real_task1.xlsx 
In this file the mean value of robot joint angles computed on the data acquired during the task1 performing for different objects positions and used to carry out the GCA-real in Tab.2 are reported (in radians) for the four patients recruited in the study.


h) GCA_real_task2.xlsx 
In this file the mean value of robot joint angles computed on the data acquired during the task2 performing for different objects positions and used to carry out the GCA-real in Tab.2 are reported (in radians) for the four patients recruited in the study.


i) GCA_real_task3.xlsx 
In this file the mean value of robot joint angles computed on the data acquired during the task3 performing for different objects positions and used to carry out the GCA-real in Tab.2 are reported (in radians) for the four patients recruited in the study.

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Additional details

Funding

European Commission
AIDE - Adaptive Multimodal Interfaces to Assist Disabled People in Daily Activities 645322