Task-Dependent Comfort Zone, a Base Placement Strategy for Mobile Manipulators Based on Manipulability Measures

The present contribution introduces the task-dependent comfort zone as a base placement strategy for mobile manipulators using different manipulability measures. Four different manipulability measures depending on end-effector velocities, forces, stiffness, and accelerations are considered. By evaluating a discrete subspace of the manipulator workspace with these manipulability measures and using image-processing algorithms, a suitable goal position for the autonomous mobile manipulator was defined within the comfort zone. This always ensures a certain manipulator manipulablity value with a lower limit with respect to the maximum possible manipulability in the discrete subspace. Results are shown for three different mobile manipulators using the velocity-dependent manipulability measure in a simulation.

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Publication Details

Journal
Robotics
Published
2024-08-16
DOI
https://doi.org/10.3390/robotics13080122
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.00
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article

Task-Dependent Comfort Zone, a Base Placement Strategy for Mobile Manipulators Based on Manipulability Measures

Martin Sereinig, Johannes Gerstmayr, Peter Manzl
Robotics
Robotic Path Planning Algorithms
article

Task-Dependent Comfort Zone, a Base Placement Strategy for Mobile Manipulators Based on Manipulability Measures

Martin Sereinig, Johannes Gerstmayr, Peter Manzl
article en

Abstract

The present contribution introduces the task-dependent comfort zone as a base placement strategy for mobile manipulators using different manipulability measures. Four different manipulability measures depending on end-effector velocities, forces, stiffness, and accelerations are considered. By evaluating a discrete subspace of the manipulator workspace with these manipulability measures and using image-processing algorithms, a suitable goal position for the autonomous mobile manipulator was defined within the comfort zone. This always ensures a certain manipulator manipulablity value with a lower limit with respect to the maximum possible manipulability in the discrete subspace. Results are shown for three different mobile manipulators using the velocity-dependent manipulability measure in a simulation.

RoboticsVol. 13(8)
Universität Innsbruck (AT)
Openalex Percentile: Top 88%
Robotic Path Planning Algorithms
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