DATEM
Monitor health and status of critical systems with machine-learning technologies
Menu
OUR CORE R&D / These systems range from individual
autonomous robotic platforms to large-scale, multi-agent systems
for information management, command & control
These systems range from individual autonomous robotic platforms to large-scale, multi-agent systems for information management, command & control
When faced with unknowns—new environments, emerging complexity, limited communications—autonomous systems must adapt to achieve their goals. Charles River’s robust autonomy algorithms and software make systems resilient by combining sensing and perception of dynamic environments with mission-level understanding and decision making.
Monitor health and status of critical systems with machine-learning technologies
A maintenance system that can predict the health and status of robotic combat vehicles
A system to explore cooperation and behavior allocation of autonomous teams
A system that detects and prevents cybersecurity breaches in military ground vehicles
Probabilistic Reasoning for System Components Onboard US Naval Vessels
Probabilistic representation of intent commitments to ensure software survival
