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Online velocity constraint adaptation for safe and efficient human-robot workspace sharing

Abstract

Despite the many advances in collaborative robotics, collaborative robot control laws remain similar to the ones used in more standard industrial robots, significantly reducing the capabilities of the robot when in proximity to a human. Improving the efficiency of collaborative robots requires revising the control approaches and modulating online and in real-time the low-level control of the robot to strictly ensure the safety of the human while guaranteeing efficient task realization. In this work, an openly simple and fast optimization based joint velocity controller is proposed which modulates the joint velocity constraints based on the robot’s braking capabilities and the separation distance. The proposed controller is validated on the 7 degrees-of-freedom Franka Emika Panda collaborative robot.
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Dates and versions

hal-02434905 , version 1 (10-01-2020)
hal-02434905 , version 2 (22-07-2020)
hal-02434905 , version 3 (18-09-2020)

Identifiers

  • HAL Id : hal-02434905 , version 3

Cite

Lucas Joseph, Joshua K. Pickard, Vincent Padois, David Daney. Online velocity constraint adaptation for safe and efficient human-robot workspace sharing. International Conference on Intelligent Robots and Systems, Oct 2020, Las Vegas, United States. ⟨hal-02434905v3⟩
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