By Topic

Hybrid dynamic mobile task allocation and reallocation methodology for distributed multi-robot coordination

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

5 Author(s)
Guanghui Li ; Department of Precision Engineering, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo, Japan ; Yusuke Tamura ; Min Wu ; Atsushi Yamashita
more authors

Dynamical mobile task allocation, by which tasks can move randomly before they are assigned robots to execute. For such a new task assignment domain, we propose a hybrid dynamic mobile task allocation and reallocation method that combines our previous proposed dynamical sequential method and global optimal method. Robots bid for tasks and transmit the costs to other robots. Then all robots select tasks from the combinatorial cost table to minimize the objective function. During the next time step, robots continue to select the assigned tasks for which costs are smaller than the set thresholds. Alternatively, robots for which costs exceed the corresponding threshold rebid unassigned tasks and transmit the calculated costs to others. The un-selected robots then re-select unassigned tasks from the combinatorial cost table according to global optimal task allocation method. In this study, the advantages of the proposed approach are demonstrated by comparison with existing task allocation methods. The simulation results demonstrate that a system implementing our method can obtain maximal accomplished efficiency of whole system and minimal executed costs for each individual robot. The negotiation time steps, communication costs and computational times are reduced using the proposed algorithm. Moreover, we believe that our method can extend the previous methods to be suitable for a large-scale distributed multi-robot coordination system.

Published in:

2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)

Date of Conference:

11-14 July 2012