By Topic

Robot task planning and trajectory learning based on programming by demonstration

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Scheer, P. ; Inst. for Aerosp. Res., Nat. Res. Council of Canada, Montreal, QC, Canada ; Alhalabi, A. ; Mantegh, I.

This paper presents a method to model and reproduce cyclic trajectories captured from human demonstrations. Heuristic algorithms are used to determine the general type of pattern, its parameters, and its kinematic profile. The pattern is described independently of the shape of the surface on which it is demonstrated. Key pattern points are identified based on changes in direction and velocity, and are then reduced based on their proximity. The results of the analysis are provided are used inside a task planning algorithm, to produce robot trajectories based on the workpiece geometries. The trajectory is output in the form of robot native language code so that it can be readily downloaded on the robot.

Published in:

Optomechatronic Technologies (ISOT), 2010 International Symposium on

Date of Conference:

25-27 Oct. 2010