Safety Assurance Adaptive Control for Modular Autonomous Vehicles
收藏ETS-Data2025-03-07 更新2026-02-07 收录
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https://doi.org/10.26599/ETSD.2025.9190004
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This study proposes a Safety Assurance Adaptive Model Predictive Control (SAAMPC) framework to achieve distributed docking/undocking operations for MAVs in uncertain environments. The SAAMPC framework integrates a Model Predictive Control (MPC) controller for trajectory optimization, an adaptive module for dynamic adjustment of control parameters with disturbance, and an adaptive safety assurance module with longitudinal and lateral Control Barrier Functions to ensure safe operation during risky and uncertain conditions. The effectiveness of the proposed approach is validated through simulations in Simulink and field tests on a reduced-scale MAV platform. Experimental results validate that the SAAMPC framework successfully ensures smooth and safe vehicle following and robust execution of docking/undocking operations under uncertainties.



