In recent years, with the continuous development of the industrial robot technology, the application of robots equipped with laser rangefinders for multipose measurement and the demand for handeye calibration have been increasing, placing higher requirements on calibration accuracy. However, traditional methods often rely on dedicated calibration objects or sensors, which are complex to operate and costly. To address this issue, this paper proposes a robot handeye calibration method based on the deep Qnetwork(DQN) algorithm and circular contour fitting. The DQN algorithm controls the two end joints of the robot to drive the laser rangefinder such that its return value is minimized. On this basis, a kinematic model of the manipulator is established to compute the theoretical coordinates of the light spot. By setting multiple angle values of joint one, the light spot forms a circular trajectory on the target plane. Circular fitting is then applied to the collected light spot coordinates, and an optimization model with equality constraints is constructed to solve for the calibration parameters. MATLAB-based simulations verified the feasibility of the method, analyzing the influence of initial values of angular and displacement parameters on calibration results, as well as robustness against laser ranging noise. Comparative experiments demonstrate that the proposed method achieves higher accuracy than other calibration approaches. An experimental system was also built, and calibration parameters were obtained using the proposed method. Experimental results show that the scanning error of the calibrated system does not exceed 05 mm, meeting the accuracy requirements of industrial applications. The method requires no additional expensive calibration objects, relying only on singlepoint measurements from the laser rangefinder and geometric constraints. It significantly reduces calibration cost and operational complexity while maintaining good noise resistance, making it well suited for highprecision industrial on-site calibration.