Swarming autonomous blimps; assured autonomy; R&D grants.
Swarming autonomous blimps
The U.S. Naval Research Laboratory (NRL) is exploring the development of miniature autonomous blimps, a technology that could pave the way towards a new form of military swarming technology.
Initially, NRL developed 30 miniature autonomous blimps. The goal is to test the interaction and swarming behavior of these autonomous systems. Georgia Institute of Technology created the blimp platforms for the Navy.
There are several use cases for swarms of autonomous systems like blimps. Targeted for both defensive and offensive military purposes, autonomous swarming technology could be used for reconnaissance, to protect an asset in the field, provide area coverage for troops, or move troops in a formation.
NRL began to study swarming behavior in the 1990s, when it devised a concept of physicomimetics. Physicomimetics is the study of physics-based swarm intelligence, which models the behavior or interaction of systems in the field. Later, NRL was inspired by biology-inspired swarms, such as bees, ants and birds.
As part of the effort, NRL is developing autonomous super swarms using miniature blimps. The goal is to fly more than 100 controlled blimps this year. One day, it hopes to devise 10,000 systems.
“We are using these as platforms to demonstrate swarm behaviors,” said Don Sofge, lead for the distributed autonomous systems group at NRL. “Behaviors are programmed into each agent individually. The idea is that each agent is making its own decisions, sensing the world around it so that the action of the group results in some desirable emergent behavior.
“In order to get the swarm to do something useful, you have to think about how to program the individual,” he said. “What behaviors or algorithms are running on the individual agent? In nature, most colony or swarm systems have no centralized control. Each individual is basically interacting with its environment, but collectively they are able to do very interesting and useful things.
“If you are working with a traditional centralized control architecture you have to deal with the challenges of communicating with 10,000 agents individually,” Sofge said. “You can’t assume everyone knows where everyone else is because they are only interacting locally based on what they sense and the decisions they are making and the actions they are taking locally.”
Assured autonomy
The Air Force Research Laboratory (AFRL) and the University of Florida have started a new research effort in the field of assured autonomy.
The university-led effort, called the Center of Excellence (COE), involves a $6 million investment by the Air Force. The COE will conduct research in the field of assured autonomy in contested environments.
The Air Force said it is interested in this field as it requires autonomous systems to execute missions “with verifiable assurances despite uncertain adversarial environments.” For this, sensor information and communications are often challenged in the field. So the goal is to develop technologies that can account for uncertainty and cyber-security.
The research team includes the University of Florida, Duke University, the University of Texas at Austin, the University of California at Santa Cruz, and the Munitions, Sensors, and Space Vehicles Directorates within AFRL.
“This COE is the scientific embodiment of basic research for assured and trustworthy autonomy of the U.S. Air Force’s future cyber physical systems operating in contested environments,” said Frederick Leve, AFOSR program officer for dynamics and control.
R&D
The U.S. Army has awarded up to $50 million to eight academic teams to pursue various research projects.
The awards are a part of the Department of Defense Multidisciplinary University Research Initiative, known as MURI.
This year’s projects include:
*How sleep clears your brain.
*Algorithmic matter and emergent computation.
*Networked palynology models of pollen and human systems.
*Near-field radiative heat transfer and energy conversion in nanogaps of nano- and meta-structured materials.
*Investigating energy efficiency, information processing and control architectures of microbial community interaction networks.
*Predicting and controlling the response of particulate systems through grain-scale engineering.
*Quantum state control of molecular collision dynamics.
*Foundations of decision making with behavioral and computational constraints.
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