Exploiting the task space redundancy in robot programming by demonstration

Tohid Alizadeh, Navab Karimi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Robot programming by demonstration (PbD) in the unstructured environment is usually a challenging task, which requires to take into account different parameters. One of the main difficulties in an unstructured environment is that the location and orientation of the objects may change dynamically, requiring the learning algorithm to posses acceptable generalization and extrapolation capabilities. There are several category of PbD approaches proposed to tackle such issues, some of which look at the objects in the environment as external parameters (task parameters, or TPs) and assume that the movement or trajectory is modulated by such objects. While, some of those TPs might not be completely observable all the time, introducing additional difficulties on the task learning. On the other hand, in specific situations two or more objects may contain similar information for the task execution. In this paper, an approach based on task-parameterized Gaussian mixture model (TP-GMM) for PbD is proposed that exploits the redundancy in the environment to deal with the partial observability of the task parameters and provide a fault tolerant approach in the sense of availability of the task parameters. The proposed approach is tested using some simulation experiments.

Original languageEnglish
Title of host publicationProceedings of 2018 IEEE International Conference on Mechatronics and Automation, ICMA 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2394-2399
Number of pages6
ISBN (Electronic)9781538660720
DOIs
Publication statusPublished - Oct 5 2018
Event15th IEEE International Conference on Mechatronics and Automation, ICMA 2018 - Changchun, China
Duration: Aug 5 2018Aug 8 2018

Publication series

NameProceedings of 2018 IEEE International Conference on Mechatronics and Automation, ICMA 2018

Conference

Conference15th IEEE International Conference on Mechatronics and Automation, ICMA 2018
Country/TerritoryChina
CityChangchun
Period8/5/188/8/18

Keywords

  • Learning by imitation
  • Redundancy in the unstructured environment
  • Robot learning
  • Robot programming by demonstration

ASJC Scopus subject areas

  • Biomedical Engineering
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Control and Optimization

Fingerprint

Dive into the research topics of 'Exploiting the task space redundancy in robot programming by demonstration'. Together they form a unique fingerprint.

Cite this