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Simultaneous haptic guidance and learning of task parameters during robotic teleoperation

Abstract : Haptic guidance can improve accuracy and dex- terity during the teleoperation of a robot, but only if the model of the task used to provide the assistance is accurate. In medical robotics, the registration of a task from pre-operative planning from medical images to the robot’s task-space can be erroneous. Additionally, the deformability of the environment can require online correction of a planned task. Therefore, we propose a method to update the geometry and the registration of a path- following task online. This model is simultaneously used to physically guide the user during the teleoperation. Experimental results obtained on a haptic interface show the validity of the approach for a simulated 2D task.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-03251658
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Submitted on : Monday, June 7, 2021 - 2:18:19 PM
Last modification on : Friday, August 5, 2022 - 3:03:30 PM
Long-term archiving on: : Wednesday, September 8, 2021 - 6:53:29 PM

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Thibault Poignonec, Florent Nageotte, Nabil Zemiti, Bernard Bayle. Simultaneous haptic guidance and learning of task parameters during robotic teleoperation. ICRA 2021 - 38th IEEE International Conference on Robotics and Automation, May 2021, Xi’an, China. pp.3619-3625, ⟨10.1109/ICRA48506.2021.9560938⟩. ⟨lirmm-03251658⟩

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