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.

A Collaborative Robotic Approach to Autonomous Pallet Jack Transportation and Positioning

Fusaro F.;Ajoudani A.
2020-01-01

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.
2020
Autonomous agents
field robots
manipulation planning
path planning for manipulators
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1149518
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