Autonomous systems can provide the Navy with valuable information about mission environments. Teams of heterogeneous autonomous vehicles may provide enhanced capabilities for persistent ISR and enhanced situational awareness for the warfighter while minimizing the risk to human life. The objective of the MANTISS (Mobile Autonomous Navy Teams for Information Surveillance and Search) effort is to apply information gathering algorithms for multi-agent autonomous teams to problems of Navy interest, leveraging bio-inspired techniques from ONR’s Science of Autonomy program, NRL-developed swarm control (physicomimetics), and information theory. Our swarm dynamics projects explore the production of self-organized states in a system of communicating robots (miniature autonomous blimps) with mass and physical extent (area or volume) such that collisions may occur. Specifically, we perform experiments to enable a formation of communicating robots to form a pattern maintained just by interacting communication rules. We study the effects of variation of controlling parameters including mass, area, and communication with number of nearest neighbors on swarm dynamics and pattern formation as agents collide and are removed. All collisions are considered catastrophic. Collisions may be reduced or avoided through use of a repulsion term between agents, but we confirm that this repulsion term affects the swarm dynamics as well. Repulsion also affects the rate of attrition of swarm agents. We evaluate the effects on pattern formation and swarm dynamics of repulsion in combination with other previously mentioned controlling parameters.
Bio:
Don Sofge is a Computer Scientist and Roboticist at the U.S. Naval Research Laboratory (NRL) with 30 years of experience in Artificial Intelligence and Control Systems R&D. He has served as PI or Co-PI on dozens of federally funded R&D programs, and has approximately 124 peer-reviewed publications on autonomy, intelligent control, quantum computing, and related topics, including 6 books, 10 book chapters, 25 journal articles, 65 conference papers, and one patent. Don leads the Distributed Autonomous Systems Group at NRL where he develops nature-inspired computing solutions to challenging problems in sensing, artificial intelligence, and control of autonomous robotic systems. His current research focuses on control of autonomous teams or swarms of robotic systems for Navy relevant missions.
]]>Autonomous systems can provide the Navy with valuable information about mission environments. Teams of heterogeneous autonomous vehicles may provide enhanced capabilities for persistent ISR and enhanced situational awareness for the warfighter while minimizing the risk to human life. The objective of the MANTISS (Mobile Autonomous Navy Teams for Information Surveillance and Search) effort is to apply information gathering algorithms for multi-agent autonomous teams to problems of Navy interest, leveraging bio-inspired techniques from ONR’s Science of Autonomy program, NRL-developed swarm control (physicomimetics), and information theory. Our swarm dynamics projects explore the production of self-organized states in a system of communicating robots (miniature autonomous blimps) with mass and physical extent (area or volume) such that collisions may occur. Specifically, we perform experiments to enable a formation of communicating robots to form a pattern maintained just by interacting communication rules. We study the effects of variation of controlling parameters including mass, area, and communication with number of nearest neighbors on swarm dynamics and pattern formation as agents collide and are removed. All collisions are considered catastrophic. Collisions may be reduced or avoided through use of a repulsion term between agents, but we confirm that this repulsion term affects the swarm dynamics as well. Repulsion also affects the rate of attrition of swarm agents. We evaluate the effects on pattern formation and swarm dynamics of repulsion in combination with other previously mentioned controlling parameters.
Bio:
Don Sofge is a Computer Scientist and Roboticist at the U.S. Naval Research Laboratory (NRL) with 30 years of experience in Artificial Intelligence and Control Systems R&D. He has served as PI or Co-PI on dozens of federally funded R&D programs, and has approximately 124 peer-reviewed publications on autonomy, intelligent control, quantum computing, and related topics, including 6 books, 10 book chapters, 25 journal articles, 65 conference papers, and one patent. Don leads the Distributed Autonomous Systems Group at NRL where he develops nature-inspired computing solutions to challenging problems in sensing, artificial intelligence, and control of autonomous robotic systems. His current research focuses on control of autonomous teams or swarms of robotic systems for Navy relevant missions.
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