Charles River Analytics Inc., developer of intelligent systems solutions, will discuss adaptive software systems at the OCEANS Conference & Exposition on October 25, 2018 in Charleston, SC. We’ll present our work on “Adapting Autonomous Ocean Vehicle Software Systems to Changing Environments.”
The event brings together 2,000 of the world’s leading marine professionals in an active coastal setting to network, collaborate, and learn about cutting-edge research and applications in the marine technology field. OCEANS 2018 is packed full of engaging presentations from leading professionals, cutting-edge research, new technology demonstrations, interactive events and activities, and more. Some highlights of the event include telecasting live from a NASA spaceship, offering tours of the historic Hunley, and hearing from renowned researchers.
Our paper furthers research on software systems onboard autonomous ocean vehicles. Systems that can adapt organically to new requirements survive longer and save the time and effort needed for manual rewrites. However, most software systems do not have this capability, and older legacy software systems are replaced as they become obsolete.
“We provide a two-part approach for imbuing legacy systems with adaptive features,” said Dr. Avi Pfeffer, Chief Scientist at Charles River. “The first part uses program analysis, where we automatically transform the source code to create adaptive parameters. Second, we optimize these parameters against a wide range of operating contexts, which expands the range of capabilities beyond the program’s original design.”
We demonstrate our approach by transforming legacy non-adaptive autonomous undersea vehicle code, where the transformation and optimization does not rely on specific semantics of the source program. Our approach may enable the expansion and optimization of a diverse variety of software systems, including autonomous ocean vehicles. Our work on software adaptation for unmanned ocean vehicles has been performed under the DARPA Building Resource Adaptive Software Systems (BRASS) program.
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This material is based upon work supported by the United States Air Force and the Defense Advanced Research Projects Agency (DARPA) under Contract No. FA8750-16-C-0045. The views, opinions and/or findings expressed are those of the author and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government.
