Time-varying Obstacle Avoidance by Using High-gain Observer and Input-to-State Constraint Safe Control Barrier Function
Issei Tezuka, Hisakazu Nakamura · IFAC-PapersOnLine · 2020
Control barrier functions (CBFs) have been studied for a state constraint problem; one of those is a human assist control for moving obstacle avoidance by using time-varying CBFs. However, the human assist control contains the complete information on the motion of environments; in general, a derivative of moving obstacle states needs estimating. In this paper, we apply a high-gain observer based differentiator to estimate a derivative of moving obstacle states. By regarding estimation errors as input disturbances, we propose an input-to-state constraint safe control barrier function (ISCSf-CBF) and construct a human assist control based on the proposed function. Moreover, we confirm the effectiveness of the proposed method by computer simulation.