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Journal of Robotics
Volume 2011 (2011), Article ID 525724, 11 pages
Research Article

Using Sun’s Java Real-Time System to Manage Behavior-Based Mobile Robot Controllers

1Department of Electrical and Computer Engineering, The University of Alabama, Tuscaloosa, AL 35487, USA
2Department of Computer Science, The University of Alabama, Tuscaloosa, AL 35487, USA

Received 7 May 2011; Revised 16 September 2011; Accepted 16 November 2011

Academic Editor: Yuan Zheng

Copyright © 2011 Andrew McKenzie et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Implementing a robot controller that can effectively manage limited resources in a deterministic, real-time manner is challenging. Behavior-based architectures that decompose autonomy into levels of intelligence are popular due to their robustness but do not provide real-time features that enforce timing constraints or support determinism. We propose an architecture and approach for using the real-time features of the Real-Time Specification for Java (RTSJ) in a behavior-based mobile robot controller to show that timing constraints affect performance. This is accomplished by extending a real-time aware architecture that explicitly enumerates timing requirements for each behavior. It is not enough to reduce latency. The usefulness of this approach is demonstrated via an implementation on Solaris 10 and the Sun Java Real-Time System (Java RTS). Experimental results are obtained using a K-team Koala robot performing path following with four composite behaviors. Experiments were conducted using several task period sets in three cases: real-time threads with the real-time garbage collector, real-time threads with the non- real-time garbage collector, and non-real-time threads with the non-real-time garbage collector. Results show that even if latency and determinism are improved, the timing of each individual behavior significantly affects task performance.