<p>In recent years, wheeled robots have been widely used in the field of logistics automation. In real-world application, the inertia of wheeled robots is not fully considered in traditional speed planning methods, and the longitudinal error of wheeled robots reaching the target area is too large to accurately complete subsequent operations, especially for large-loaded wheeled robots like autonomous forklifts. In order to deal with the above problem, this paper proposes an acceleration-awarded speed planning method based on acceleration optimization aimed at making wheeled robots reach the target area smoothly and accurately. This method first introduces acceleration information into speed planning based on dynamic constraints, and then models speed planning as an optimization problem to smooth speed changes. Experimental verification shows that the longitudinal error of wheeled robots using this method is significantly reduced, and the smoothness of speed is improved.</p>