Abstract
This paper proposes a novel loco-manipulation control framework for the execution of complex tasks with kinodynamic constraints using mobile manipulators. As a representative example, we consider the handling and re-positioning of pallet jacks (or lifts/carriers with similar characteristics) in unstructured environments. This task is associated with significant challenges in terms of locomotion, due to the mobility constraints that are imposed by their limited kinematics while moving, and manipulation, due to the existence of dynamic uncertainties while grasping and handling of pallet jacks. To tackle these challenges, our solution enables the robotic platform to autonomously reach a pallet jack location while avoiding the obstacles, and to detect and manipulate its handle by fusing the perception and the contact force data. Subsequently, the transportation of the pallet jack is achieved through a whole-body impedance controller and a trajectory planner which takes into account the mobility constraints of the robot-pallet jack chain. We demonstrate the effectiveness of the proposed solution in reaching and displacing the pallets to desired locations through simulation studies and experimental results. While these results reveal with a proof-of-concept the effectiveness of the proposed framework, they also demonstrate the high potential of mobile manipulators for relieving human workers from such repetitive and labor intensive tasks. We believe that this extended functionality can contribute to increasing the usability of mobile manipulators in different application scenarios.
Highlights
The role of automation in logistics has been growing more and more in the last decades
Towards understanding the potential of cobots in addressing the pallet management problem, in this work, we propose a novel autonomous pallet jack repositioning framework by means of a MObile Collaborative robotic Assistant (MOCA) [16]
The proposed framework can navigate a mobile cobot to a target pose, detect the handle of the pallet jack and approach to grasp it, and transport it to a desired position and orientation in a warehouse environment
Summary
The role of automation in logistics has been growing more and more in the last decades This is due to the increasing demands imposed by the ‘‘e-commerce revolution’’ [1], whose constant progress cannot be responded by the decreasing available workforce in aging societies. The existing solutions require large initial investments, since they often need to be applied to customized production processes These solutions are not flexible enough, so they can be hardly employed in dynamically changing environments such as small and medium sized warehouses. For this reason, only 5% of the existing warehouses worldwide have been semi-automated [3]
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