Limited-Information Cooperative Shared Control for Vehicle-Manipulators

Abstract

This paper presents a novel cooperative control algorithm for vehicle-manipulators (VMs) with a human operator. VMs usually operate in unstructured environments, which means that a full automation of the overall system, combing a vehicle and a robotic manipulator is currently very challenging. Therefore, human operator controlled VMs are state-of-the-art. With current developments in autonomous driving, the automation of the vehicle platform is within reach. A cooperative shared control between the autonomous platform and the human controlled manipulator can happen through the coupling motion between the vehicle platform and the manipulator. An autonomous vehicle platform can furthermore be used to support the human operator with the control of the manipulator. However, the future trajectory of the manipulator intended by the human operator is in general not known to the autonomous vehicle. The main question is thus how the autonomous vehicle should act in order to support the human controlled manipulator in following its unknown trajectory. To solve this problem, we propose an approach that characterizes the cooperation and the unknown errors with an algebraic equation. The novel approach is compared to cooperative control methods with known errors of the manipulator, based on the theory of differential games. The benefits of the proposed method are that no sensors for the environment perception and for the state measurements of the manipulator are necessary, which are demonstrated in simulations.