PERATON LABS AWARDED DARPA CONTRACT FOR REAL-TIME ADAPTIVE CONTROL OF PHYSICAL SYSTEMS

Peraton Labs has been awarded a DARPA contract to develop machine learning-based technology to enable ground vehicles, ships, drone swarms, robotic systems, and other long-lived physical systems to adapt to unexpected events. Under DARPA’s Learning Introspective Control program, the Peraton Labs team will develop and evaluate the capability to update the system control algorithm in real time and provide guidance to the system’s human operator or autonomous controller.

Peraton Labs will research, design, implement, and test a solution called Adaptive Control with AI (ACAI) to assist operators, human or machine, in maintaining control of systems in adverse situations.

ACAI leverages data from on-board sensors and applies a sophisticated combination of machine learning, constrained optimization, and a robust optimal control framework to select optimal controls based on the current system state and environmental conditions. ACAI’s intelligent control algorithm coordinates between performance and safety to provide high-performance controls while also maintaining the safety and stability of the system.