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Simultaneous haptic guidance and learning of task parameters during robotic teleoperation

Abstract : Haptic guidance can improve accuracy and dexterity 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 pathfollowing 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
Contributor : Nabil Zemiti <>
Submitted on : Monday, June 7, 2021 - 2:18:19 PM
Last modification on : Tuesday, June 8, 2021 - 3:38:19 AM

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  • HAL Id : lirmm-03251658, version 1

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Thibault Poignonec, Florent Nageotte, Nabil Zemiti, Bernard Bayle. Simultaneous haptic guidance and learning of task parameters during robotic teleoperation. International Conference on Robotics and Automation (ICRA 2021), IEEE, May 2021, Xi’an, China. ⟨lirmm-03251658⟩

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