The 3rd Offset Strategy
The Secretary of Defense established the 3rd Offset Strategy to set the nation's strategic defense priorities for the next 25 years. The strategy calls for the development and deployment of autonomous systems and deep learning, human machine collaboration, and advanced human machine teaming. In support of this strategy, Shield AI's delivers GPS-denied navigation, mapping, exploration, multi-robot collaboration, robot interfaces, and target detection and tracking capabilities.
Autonomy & Deep Learning
Autonomy enables large scale deployment of robotics to the battlefield. To enable autonomy, Shield AI gives robots the ability to understand their environment and make intelligent choices without a remote pilot. Principled algorithms fused with deep neural networks enable never-before seen robotic capabilities that can dramatically improve outcomes and reduce risk. Our robots perceive their surroundings, and therefore they can explore, interact with, and collect intelligence in their environment with minimal human oversight.
Human machine collaboration
Trust is fundamental to the success of teams whether they are human, robotic, or mixed. We implement algorithms and train robots to complete complex tasks while behaving in expected ways to earn the trust of human collaborators. Whether the objective is to provide force protection or intelligence for base defense, patrols, or close quarters combat; our robots collaborate with service members to ensure a significant reduction in risk to friendly forces, innocent civilians, and the mission.
Advanced human machine teaming
We employ swarms of robots that team with service members to accomplish several different mission sets, but not at the expense of additional cognitive demand on the user. Service members in the field must only receive the most important notifications from a robot swarm for human machine teams to be truly effective. Shield AI is developing cutting edge approaches to multi-agent exploration that are designed to enable a scaleable number of robots to efficiently find threats to service members while maintaining network connectivity. A simple, seamless human machine interface that minimizes required cognitive demand is used to command the robot swarm.