By Topic

A Potential Field Model Using Generalized Sigmoid Functions

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
$33 $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

4 Author(s)
Jing Ren ; Fac. of Eng., Univ. of Ontario Inst. of Technol., Oshawa, Ont. ; Kenneth A. McIsaac ; Rajni V. Patel ; Terry M. Peters

The lack of a potential field model capable of providing accurate representations of objects of arbitrary shapes is considered one major limitation in applying the artificial potential field method in many practical applications. In this correspondence, we propose a potential function based on generalized sigmoid functions. The generalized sigmoid model can be constructed from combinations of implicit primitives or from sampled surface data. The constructed potential field model can achieve an accurate analytic description of objects in two or three dimensions and requires very modest computation at run time. In this correspondence, applications of the generalized sigmoid model in path-planning tasks for mobile robots and in haptic feedback tasks are presented. The validation results in this correspondence show that the model can effectively allow the user or mobile robot to avoid penetrations of obstacles while successfully accomplishing the task

Published in:

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)  (Volume:37 ,  Issue: 2 )