Collaborative Tracking Control Strategy for Autonomous Excavation of a Hydraulic Excavator

A hydraulic excavator consists of multiple electrohydraulic actuators (EHA). Due to uncertainties and nonlinearities in EHAs, it is challenging to devise a proper control strategy. To tackle this issue, a major goal of our study is to provide an efficient control strategy to minimize tracking errors of the bucket tip position for autonomous excavation. To accomplish the goal, the study offers a collaboration of PID and fuzzy controllers that are used to compensate for contour errors and achieve accurate actuator position control, respectively. Co-simulation models including control algorithms and hydraulic components were created using Matlab and Amesim to validate the performance of the designed controllers. Simulations indicate that the proposed method enables achieving accurate tracking control for autonomous excavation with small tracking errors despite the nonlinear characteristics of the hydraulic excavator system.

Moving target tracking method for unmanned aerial vehicle/unmanned ground vehicle heterogeneous system based on AprilTags

Using the characteristics of unmanned aerial vehicle/unmanned ground vehicle, heterogeneous systems can accomplish many complex tasks cooperatively. Moving target tracking is an important basis for the relative positioning and formation maintenance of heterogeneous cooperative systems. This paper first introduces the unmanned aerial vehicle/unmanned ground vehicle collaborative tracking task and heterogeneous system. In order to maintain the original stability of unmanned aerial vehicle, a control method based on SBUS protocol to simulate remote control is proposed. About unmanned ground vehicle with Mecanum wheel, a detailed description of control method is designed. For the problems of real-time performance and occlusion, a tracking scheme based on AprilTag identification is studied. The scheme tracks the Tag target in the case of no occlusion. When occlusion occurs, the scheme tracks the color feature around the Tag. The accuracy of the tracking algorithm and the problem of occlusion are greatly improved. Finally, the scheme is applied to the heterogeneous systems. Simulation and experimental results show that the proposed method is suitable for unmanned aerial vehicle/unmanned ground vehicle heterogeneous system to perform the collaborative tracking task.