An Inverse Kinematics Algorithm With Smooth Task Switching for Redundant Robots
Hannes Gamper (CERN, Johannes Kepler University Linz)
Laura Rodrigo Rodrigo Pérez (CERN)
Andreas Mueller (Johannes Kepler University Linz)
Alejandro Díaz Rosales (CERN, TU Delft - Human-Robot Interaction)
Mario Di Castro (CERN)
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Abstract
This letter presents an inverse kinematics approach that combines two well-known Jacobian based methods, the task-priority framework and an optimization-based approach, such that tracking and optimization tasks can be executed simultaneously. The novelty of the proposed algorithm lies in the ability to smoothly switch between different tasks and thus to allow for a seamless and safe transition during robot operation. This has shown to improve the efficiency and user experience, especially during tele-operated interventions in complex environments.