Hierarchical coordinated control distribution and experimental verification for six-wheeled unmanned ground vehicles

In recent years, the all-wheel independent drive has been the most promising form of drive configuration in unmanned ground vehicles. Considering the difficulties in the control allocation for this kind of vehicle, this paper presents a hierarchical control coordination strategy with three layers to distribute control in real time effectively and accurately. In the upper layer, a hybrid instruction parsing method is proposed, which converts commands of the control panel into driving force requirement and target steering yaw rate, respectively, to prioritize steering command to maintain the trajectory based on the motor properties. Subsequently, a sliding mode controller is employed to convert the target yaw rate into the required yaw moment. The state estimation layer receives data from the sensors and estimates different properties/parameters required in other layers. The lower-level control layer receives commands from the upper layer and allocates respective control to wheels. The control allocation problem has been formulated as an optimization problem and later has been converted into a quadratic programming problem, in which a novel modified barrier method with the combination of reduced equation dimension has been adopted to minimize the computational effort and complexity for implementation on the embedded platform. Computer simulation and field experiment have been conducted, which verify the performance of the proposed strategy.