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It is easy to collide with external obstacles in the process of robot movement. when the collision force is too large, it will cause damage to machine parts. to solve this problem, a robot collision pre estimation controller based on ai depth learning is designed. The human-computer interaction circuit and serial communication circuit are established. The servo motor equipment, motion controller and PC induction device are respectively connected to the given action area to complete the overall application structure design of the pre estimation controller. Based on the PyTorch depth learning framework, the activation function is defined, and then the accurate detection of the target robot object is realized according to the actual value range of the pre estimated parameters. According to the torque control condition expression, the performance strength of the collision behavior is determined, the robot motion path planning is completed, and the robot collision pre estimation controller design based on ai depth learning is realized by combining relevant application equipment. The experimental results show that under the action of ai depth learning algorithm, the contact area of the collision part between the robot and the obstacle will not exceed 0.25m2, and the external force caused by the collision behavior is relatively small, which will not cause serious damage to machine parts.