Aimed at improving the low measurement accuracy of the binocular vision sensor along the optical axis in the process of target tracking, we proposed a method for auxiliary correction using a laser-ranging sensor in this paper. In the process of system measurement, limited to the mechanical performance of the two-dimensional turntable, the measurement value of a laser-ranging sensor is lagged. In this paper, the lag information is updated directly to solve the time delay. Moreover, in order to give full play to the advantages of binocular vision sensors and laser-ranging sensors in target tracking, federated filtering is used to improve the information utilization and measurement accuracy and to solve the estimated correlation. The experimental results show that the real-time and measurement accuracy of the laser ranging-assisted binocular visual-tracking system is improved by the direct update algorithm and the federal filtering algorithm. The results of this paper are significant for binocular vision sensors and laser-ranging sensors in engineering applications involving target tracking systems.

Abrasive belt has the advantages of high removal efficiency and high waste collection; furthermore, it does not easily damage the rail when applied in rail grinding. However, the poor wear consistency and short service life restrict its development in this field. It is important to explore the theory and technology of monitoring the abrasive belt wear condition to evaluate the means of improving the grinding performance of the belt. This article discusses the contact stress state between the belt and the rail surface. In addition, the study establishes the belt rail grinding force model during operation using the abrasive grain distribution function. The analysis of the force model proposes that the belt abrasion condition be monitored by using the force ratio parameter of the abrasive belt in the grinding process. The extraction method of the force ratio information is proposed in accordance with the grinding environment. The results of experiments successfully verified the validity of the method.

Base stability for a wheeled robot while driving over rough terrain is a challenging issue. This paper proposes a novel base-stability control framework, consisting of an AVIC (adaptive variable-impedance control), AVIC-based tracking controller, and a THV (terrain height variation) and AC (attitude control) AC-based controller to stabilize the base on rough terrain. The AVIC-based controller aims to track the desired trajectory of the robot base while suppressing lumped disturbance, including system uncertainties in the internal dynamics and unknown external disturbance. The THV-based controller is utilized as a feedforward controller to improve posture tracking performance in order to achieve a horizontal posture. The AC-based controller is employed to maintain the horizontal posture of the base. The effectiveness and robustness of the proposed controllers are validated by a series of numerical trials, and the results are evaluated.