Collaborative Mission Autonomy

Multi-Platform and Multi-Domain Autonomy Solutions

At Scientific Systems, we’ve created a revolutionary autonomy software platform based on the science of behavioral robotics. With Collaborative Mission Autonomy (CMA) onboard, autonomous platforms can be powered by artificial intelligence to dramatically shorten OODA-loop cycles. Collaborative Mission Autonomy enables:

INTELLIGENT CONTROL DECISIONS

Make independent, intelligent control decisions based on commander’s intent, rules of engagement, and contextual environment data. We uniquely couple artificial intelligence methods such as neural networks and machine learning with our CMA engine in order to maximize capabilities in complex and uncontrolled environments.

COORDINATION ACROSS SYSTEMS

Coordinate in a synchronized fashion with many other AI-enabled autonomous and manned systems in and across domains. Powerfully, CMA assumes reliable high-bandwidth communications will not be available in the teaming network, providing both efficiency and resiliency.

HUMAN SUPERVISION

Exercise human control at a supervisory level in accordance with current policy, strategy, doctrine, operational requirements, and tactical procedures. With command and control at the mission level, CMA provides the ability of single operators to manage tens to even hundreds of unmanned platforms in and across domains.

Power Large-Scale Mission Architectures

Collaborative Mission Autonomy integrates across a large numbers of manned and unmanned platforms. This transcends sensor fusion by enabling a dynamic “system of services” integration and orchestration. Using CMA you can direct autonomous platforms to maximize sensor payload performance, and then direct the most valuable information to assets that need it the most. This accelerates the timeline from intake to action, rapidly speeding up OODA loop cycles, when milliseconds matter.

The unique, modularized architecture of Scientific Systems’ Collaborative Mission Autonomy technology allows it to be integrated onto a variety of new and legacy unmanned platforms, with minimal impacts to those systems. At the same time it enables a variety of advanced AI-based software components to be rapidly integrated and utilized to direct autonomous decision making for ever-changing missions.

Highlights of SSCI CMA Development

(2018 Q1)

Contact the Scientific Systems Team

Are you interested in learning more about AI-enabled autonomous capabilities to meet your particular requirements? Contact a member of the Scientific System team for more information.