Autonomous Capability

Autonomous capability research focuses on enabling machines to perform complex tasks independently, adapting to dynamic environments and handling uncertainties. Current efforts concentrate on developing robust control systems using reinforcement learning, deep learning, and hierarchical learning architectures, often incorporating human-in-the-loop elements for safety and oversight. This field is crucial for advancing applications in diverse sectors, including space exploration, search and rescue, industrial automation, and transportation, by improving efficiency, safety, and resilience in challenging or hazardous conditions. The development of quantitative frameworks for assessing autonomy levels is also a key area of ongoing research.