This paper addresses the problem of pallet picking by an Articulated-Frame-Steering (AFS) hydraulic machine. We propose a macro-micro visual mobile manipulation architecture, where a smooth switching logic navigates the robot to pick an object. The state space is divided into several regions depending on the accuracy of the vision and robot's degrees of freedom. The control architecture benefits from the following phenomena: at distance, when the location of the object of interest is detected, its orientation may not be reliably estimated; at some closer distances, orientations also become available; and because pallets are wide with small height, yaw angle estimation are more accurate than pitch is. The switching logic is devised to control the corresponding degree of freedom of the mobile manipulator in each region. Moreover, in different regions, we employ different coordinate frames, namely an earth-fixed frame or an object-local frame, which is more natural for the problem in that region. We show that the architecture accomplishes the following: 1) it eliminates the need for replanning as the accuracy of pose estimation improves; and 2) it provides the mobile base with a longer corridor to steer toward the pallet and align its heading. We also incorporate a robust, accurate solution based on fiducial markers for object manipulation in unstructured outdoor environments and unfavorable weather conditions, which relies solely on a monocular camera for pallet detection. The presented experimental results demonstrate the superiority of the method, as the model starts following the target even when the pallet is still 6m away from the vehicle.
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