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The network employs attention\u2010based path optimization to generate the predictive path. Herein, the robot's safety is considered as a hard constraint, and the control barrier function constraint is used to design the collision loss. Additionally, a deep constraint correction module is designed to correct the predictive path, which aims to make the path satisfy the constraints. Herein, the approach through simulation and real\u2010world experiments is tested to verify the function of each module. 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