Force Distribution and Estimation for Cooperative Transportation Control on Multiple Unmanned Ground Vehicles.

Abstract

This article presents an effective design of omnidirectional four-mecanum-wheeled vehicles to transport an object and track a predefined trajectory cooperatively. Furthermore, a novel design of the rotary platform is presented for multiple unmanned ground vehicles (m-UGVs) to load objects and provide better maneuverability in confined spaces during cooperative transportation. The number of unmanned ground vehicles (UGVs) is adjustable according to the object's weight and size in the proposed framework because transportation is accomplished without physical grippers. Moreover, to minimize the complexity in dealing with the interactive force between the object and UGVs, no force/torque sensor is used in the design of the control algorithm. Instead, an adaptive sliding-mode controller is formulated to cope with the dynamic uncertainties and smoothly transport an object along a desired trajectory. Thus, three external force analyses-gradient projection method, adaptive force estimation, and radial basis function neural network force estimation-are proposed for m-UGVs. In addition, the stability and the performance tracking of the m-UGV system in the presence of dynamic uncertainties using the proposed force estimation are investigated by employing the Lyapunov theory. Finally, experiments on cooperative transportation are presented to demonstrate the efficiency and efficacy of the m-UGV system.