A motion planning method based on the angular velocity and linear velocity generated by the convex optimized smoothing dynamic window approach is proposed for the problem that the angular velocity and linear velocity sequences generated by the traditional dynamic window approach fluctuate frequently and cannot control the normal motion of the robot due to the rugged road surface under the coal mine. Firstly, the dynamic window method is used to generate a set of angular velocity linear velocity sequences, then the objective function is constructed based on this sequence to obtain the optimal solution using convex optimization to remove the noise in the original sequence and achieve the motion control of the robot, and the obtained optimal solution is the smoothed angular velocity linear velocity sequence. Finally, simulations are performed using matlab to verify the smoothing effect of convex optimization under different maps and to compare with mean filtering and VMD reconstruction of the signal. The results show that, compared with the comparison algorithms, the convex optimized dynamic window method has the best smoothing effect on the angular and linear velocity sequences with the smallest average absolute errors of 0. 005 6 and 0. 001 8, smoothing the signal while preserving its characteristics.