Phase II year
2022
(last award dollars: 1695294848)
Phase II Amount
$1,499,990
[8:25 AM] Bo Ryu for SQUIRREL: Squads of soldiers operating in dense foliage environments, such as triple-canopy jungle, need to be able to move at will through the environment in the most flexible way possible while still maintaining communication within-team and with higher echelons. Within-team communication allows team members to provide individual status, maintain situational awareness, and coordinate activity. Reachback communication allows teams to provide team status, maintain situational awareness, and receive information and directives from higher command. Because these types of communication are critical to mission success, and because dense foliage environments attenuate RF signals beyond what is typically encountered in many parts of the world, a solution to support this mission environment is vital. Solutions should include a flexible, self-positioning, self-healing, three-dimensional mesh network that supports variable mission durations while exhibiting characteristics of interest to the military, such as low noise, low observability, low probability of intercept, and low probability of detection. Solutions should also require soldiers to expend the minimal amount of effort creating and maintaining this communication network. Solutions should allow for the formation and maintenance of the network by autonomous robots serving as radio relays in support of their human counterparts. This swarm of autonomous robots should also be able to exploit RF-MG which will improve communication (e.g., link quality and throughput) between nodes. We propose RF-guided Tactical AI Optimized Under Canopy Autonomous Networks (RF-TOUCAN), a swarm of small, autonomous flying drones, that are capable of creating a 3D mesh network in a dense foliage environment through a combination of macro- and micro-positioning actions as well as cognitive radio networking functions to support the mission characteristics and objectives. Macro-positioning includes selecting the optimal positions in a large 3D space to reach neighboring nodes; micro-positioning includes selecting the optimal position in a small 3D region in which to perch while exploiting RF-MG. Meanwhile, cognitive radio/networking functions allow additional degrees of flexibility to achieve robust communication. These algorithms can be adjusted to support different mission scenarios or priorities. We anticipate that the largest market for the RF-TOUCAN system will be the US and allied government market. Focusing primarily on the defense applications, small ground teams will adopt the RF-TOUCAN system to maintain better intra-team communication, improving mission effectiveness and survivability in complex, contested environments. The reachback functionality provided by RF-TOUCAN will allow continuous integration with asymmetric US and allied capabilities such as intelligence, air or indirect fires, resupply, and rapid infiltration/exfiltration.
