A human-inspired subgoal-based approach to constrained optimal control

This paper investigates the application of human motion guidance principles to the development of an autonomous guidance process. Primarily, it extends previous work, which identifies the organization of human guidance performance given by trajectory data. First, the paper describes interaction patterns (IP), subgoals, and partitions and defines these elements in terms of control theoretical concepts. Second, IPs are applied to form a computational solution to a constrained optimal control problem and simulation results demonstrate that this approach produces feasible solutions. Finally, first-person human experimental results are provided to validate theoretical concepts.