By Topic

Formation Control for Mobile Robots in partially known Environments using Mixed Integer Programming and Fuzzy Systems

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

4 Author(s)
Kopfstedt, T. ; Dept. of Res. & Dev., Diehl BGT Defence, Ueberlingen ; Mukai, M. ; Fujita, M. ; Sawodny, O.

We consider a setting where a team of multiple robots has to fulfil a mission in a specifically defined formation in a partially known environment. In many real environments, not all obstacles are previously known, but often most of them. For the planning of the optimal trajectory along these obstacles a mixed integer programming algorithm is used. If during the mission at least one of the robots detects a previously unknown obstacle, the control on each robot switches from centralized formation control to decentralized control. In this case, each robot is able to use its own set of fuzzy systems for obstacle avoidance and returns to the optimal trajectory after passing the unknown obstacles. This concept allows the robots to find the optimal trajectories for the mission task in known areas using the mixed integer programming. In unknown or for the mixed integer programming too complex scenarios the robots have to use the information based on their limited onboard sensors. With the sensor information they are in most cases able to find at least a possible way through the obstacles by using a set of onboard fuzzy systems for robot control

Published in:

SICE-ICASE, 2006. International Joint Conference

Date of Conference:

18-21 Oct. 2006