Combined Kinematic and Dynamic Control of Vehicle-Manipulator Systems
Peer reviewed, Journal article
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A vehicle-manipulator system (VMS) is a class of mobile robots characterised by their ability to carry or be a robotic arm and therefore also manipulate objects. The VMS class includes vehicles with a robotic manipulator, free-floating space robots, aerial manipulators and underwater vehicle-manipulator systems (UVMSs). All of these systems need a kinematic controller to solve the kinematic redundancy of the VMS and a dynamic controller to follow the reference given by the kinematic controller. In this paper, we propose a combined kinematic and dynamic control approach for VMSs. The approach uses the singularity-robust multiple task-priority (SRMTP) framework to generate a velocity reference combined with a dynamic velocity controller based on a robust sliding mode controller (SMC). Any SMC can be used as long as it can make the velocity vector converge to the velocity reference vector in finite time. This novel approach allows us to analyse the stability properties of the kinematic and dynamic subsystems together in the presence of model uncertainty. We show that the multiple set-point regulation tasks will converge asymptotically to zero without the strict requirement that the velocities are perfectly controlled. This novel approach thus avoids the assumption of perfect dynamic control that is common in kinematic stability analyses for robot manipulators. We present two examples of SMCs that can make the velocity vector converge to the velocity reference vector in finite time. We also demonstrate the applicability of the proposed approach through a simulation study of an articulated intervention-AUV (AIAUV), which is a type of UVMS, by conducting three simultaneous tasks. The results show that both SMC algorithms can make all the regulation tasks converge to their respective set-points. In the simulation study, we also include the results from two standard control methods, a proportional-integral-derivative (PID) controller and a feedback linearisation controller, and we use two different AIAUVs to illustrate the advantages and robustness achieved from using SMC.