Abstract | ||
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A Python module for rapid prototyping of constraint-based closed-loop inverse kinematics controllers is presented. The module allows for combining multiple tasks that are resolved with a quadratic, nonlinear, or model predictive optimization-based approach, or a set-based task-priority inverse kinematics approach. The optimization-based approaches are described relation to the set-based task approach, and a novel multidimensional in tangent cone function is presented for set-based tasks. A ROS component is provided, and the controllers are tested with matching a pose using either transformation matrices or dual quaternions, trajectory tracking while remaining a bounded workspace, maximizing manipulability during a tracking task, tracking an input markeru0027s position, and force compliance. |
Year | Venue | DocType |
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2019 | arXiv: Robotics | Journal |
Volume | Citations | PageRank |
abs/1901.06713 | 0 | 0.34 |
References | Authors | |
0 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Mathias Hauan Arbo | 1 | 1 | 2.09 |
Esten I. Grøtli | 2 | 118 | 12.96 |
Jan Tommy Gravdahl | 3 | 327 | 43.60 |