Adaptive Planning

Adaptive planning focuses on developing systems capable of dynamically adjusting plans in response to unforeseen events or changing environments, aiming for robust and efficient decision-making. Current research emphasizes integrating generative models, particularly deep learning architectures like deep ensembles, with planning algorithms such as Dijkstra's algorithm and techniques leveraging Planning Domain Definition Language (PDDL) descriptions, often informed by Model-Based Systems Engineering (MBSE). This field is crucial for advancing autonomy in diverse applications, from robotic navigation and assistive care to planetary exploration and autonomous racing, by enabling more resilient and adaptable systems in complex and uncertain settings.