COMPANY

WHO WE ARE

MISSION

Engineering Science Into Solutions

At Scientific Systems, we develop advanced technologies for navigation, mission planning and AI-enabled autonomy systems for the Aerospace and Defense industries. Our solutions enable unmanned systems across air, ground, maritime and space domains to implement Commander’s Intent, ensure mission effectiveness, and dramatically shorten operational timelines.

Why We Do It

Improving Mission
Outcomes

Today’s front line isn’t clearly marked in the sand. The battlespace is multi-domain, over air, land, sea and space. Mission success requires creative thinking and the integration of disparate systems into a unified and collaborative force.

At Scientific Systems, we advance the possibilities of mission autonomy through pioneering innovations in navigation, mission planning and autonomous systems to shorten operational timelines and dramatically improve outcomes in difficult environments.

Timeline: 1970’s to Today

Company Milestones

Founded in 1976, we’ve delivered more than 40 years of continuous innovation. Many of these achievements are outlined in the timeline below. We invite you to see the path we’ve travelled to become the industry leader in AI-enabled mission autonomy. Click the dates to discover accomplishments for each decade.

1976 – 1980

Application of Bifurcation Analysis and Chaos Theory Methodology (BACTM) to Aircraft Dynamics at High Angles of Attack (later extended to engine stall)
Nonlinear Dynamic System Identification using Statistical Machine Learning (1976-1978) – Used model structure similar to Neural Networks

First SBIR contract from NSF in 1978 (Holter mentoring using automated ECG analysis)

First application of Model Predictive Control (MPC) to F100 Jet Engine Control (1978).

1980 – 1990

1990 – 2000

Aircraft Adaptive Flutter Suppression
Aircraft and Rotorcraft flexible mode identification and control
Multi-target tracking, Superresolution and Automatic Target Recognition for Joint STAR and AWACS aircrafts
Intrusion Detection Systems for Network Cybersecurity

Model Predictive Control (MPC) for single and multiple spacecraft formation flying
Reinforcement Learning for communication network management

2000 – 2010

Autonomous control of UAVs and UCAVs (ONR)
Shipboard landing of UAVs
Genetic based Machine Learning, (GBML) applied to air combat
Reinforcement Learning applications for communication networks management
Collaborative Autonomy for unmanned vehicles (CNAV- underwater)

Spacecraft and UAV formation flying
Sense and Avoid systems
ImageNav for GPS- denied Navigation
FOPEN target tracking
Space Situational Awareness and Defense of space assets
Swarm control and state estimation

2010 – Current

Unmanned Surface Vessel Adversarial Autonomy
A SBIR to develop new AI-enabled algorithms to model adversarial behaviors in a maritime environment.
DBM
Cutting-edge, semi-autonomous software in a category called Distributed Battle Management (DBM).
SquadX
System prototyping for point of departure, ensuring squad members can communicate between unmanned systems.
FLA
The Fast Lightweight Autonomy (FLA) program is bringing a fresh approach to reactive navigation to assist small combat units.
CODE
The Collaborative Operations in Denied Environment (CODE) program aims to use swarms of UAVs working under hostile environments to collect and transmit real-time information.
Blackjack
The Blackjack program develops and demonstrates technical elements for building a global high-speed network backbone in low earth orbit (LEO).

URSA
URSA develops technology to enable autonomous systems to detect hostile forces and establish positive identification of combatants before U.S. troops encounter them.
SWIFT
Unique capability integrating acoustic sensing and fully autonomous UAV indications and warning technology.
ImageNav (SDB-1 Testing)
Successful drop testing of the SDB-1 munition using image-based navigation.
COCA
A model based approach for rapid development and integration of ImageNav capabilities onto a variety of platforms.
INAV-SL (transition program)
INAV‐SL is anl optical‐based landing system that uses pilot visual landing aids (VLA) to land in a range of conditions.
Significant SBIRs (NASA phase 2s Safesee, Machine Learning and AI (XDATA, PPAML)
Scientific Systems is leading the next generation of Space Based Infrared Surveillance with a number of current projects.
Trident Spectre Demo, MUMT, CDMaST, Mine Detection, PANAMA
Scientific Systems is currently involved in a number of projects enhancing the intelligence for unmanned vehicles.

Leadership

Meet the Executive Team

Our world-class scientists, engineers and technical architects hold decades of experience across the full spectrum of engineering, software development and management disciplines. Learn more about their roles, backgrounds and expertise.

MEET LEADERSHIP

Scientific Systems advances the possibilities of mission autonomy through pioneering innovations in navigation, mission planning and autonomous systems. Our solutions enable unmanned systems to implement commander’s intent, ensure mission effectiveness, and dramatically shorten operational timelines.

Transition Division ISO 9001:2015 Certified

CONTACT

500 West Cummings Park, Suite 3000, Woburn, MA 01801
(781) 933 – 5355