Our future military force will be complex: a highly integrated mix of manned and unmanned units. These unmanned units could function individually or within a swarm. The readiness of future warfighters to work alongside and utilize these new forces depends on the creation of usable interfaces and training simulators. The difficulty is that current unmanned aerial vehicle (UAV) control interfaces require too much operator attention, and common swarm control methods require expensive computational power. This paper begins with a discussion on how to improve upon current user interfaces and then reviews a swarm control method, the digital pheromone field. This method uses digital pheromones to bias the movements of individual units within a swarm toward areas that are attractive and away from areas that are dangerous or unattractive. Next, a more efficient method for performing pheromone field calculations is introduced, one that harnesses the power of the graphics processing unit (GPU) in today's graphics cards by reshaping the ADAPTIV swarm control algorithm into a form acceptable to the GPU's pipeline [1]. The GPU ADAPTIV implementation is tested in scenarios that involve up to 50,000 virtual UAVs. When compared to its counterpart CPU implementation, the GPU version performed over 30 times faster than the CPU version. This gain translates directly into lower costs for training the future warfighter today and fielding the swarms of tomorrow. Finally, this paper presents a vision of how to combine these new interface ideas and performance enhancements into an effective swarm control interface and training simulator. ABSTRACTOur future military force will be complex: a highly integrated mix of manned and unmanned units. These unmanned units could function individually or within a swarm. The readiness of future warfighters to work alongside and utilize these new forces depends on the creation of usable interfaces and training simulators.The difficulty is that current UAV control interfaces require too much operator attention and common swarm control methods require expensive computational power. This paper begins with a discussion on how to improve upon current user interfaces and then reviews a swarm control method, the digital pheromone field. This method uses digital pheromones to bias the movements of individual units within a swarm toward areas that are attractive and away from areas that are dangerous or unattractive. Next, a more efficient method for performing pheromone field calculations is introduced, one that harnesses the power of the GPU (graphics processing unit) in today's graphics cards by reshaping the ADAPTIV swarm control algorithm into a form acceptable to the GPU's pipeline (Parunak et al, 2002). The GPU ADAPTIV implementation is tested in scenarios that involve up to 50,000 virtual UAVs. When compared to its counterpart CPU implementation, the GPU version performed over 30 times faster than the CPU version. This gain translates directly into lower costs for training the future warfight...
A new design for an immersive ground control station is presented that allows operators to monitor and control one or more semi-autonomous unmanned remote vehicles. This new ground station utilizes a virtual reality based visualization of the operational space and the graphical representation of multiple information streams to create a comprehensive immersive environment designed to significantly enhance the operator's situational awareness over present generation "soda straw" optical systems. The environment simultaneously informs the operator about the position and condition of the vehicles under his or her control while providing an organizing context for the available information relevant to the engagement. The work on this new control station combines results from an Air Force Research Lab sponsored project in immersive joint battlespace visualization and a new virtual reality teleoperation control architecture. The technique is applicable to a range of vehicles including unmanned aerial vehicles (UAVs), unmanned combat aerial vehicles (UCAVs), unmanned border patrol vehicles, and unmanned search and rescue vehicles. An architecture for virtual reality aided teleoperation is presented as well as its implementation in software and results of a preliminary user test that compared this approach to a more traditional optical teleoperation system. The paper concludes with a discussion of how this new teleoperation system could evolve into a next generation UAV ground control station.
No abstract
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.