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A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
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Dynamic modelling and predictive position/force control of a plant-inspired growing robot.

Abdonoor Kalibala1, Ayman A Nada1, Hiroyuki Ishii2

  • 1Department of Mechatronics and Robotics Engineering, Egypt-Japan University of Science and Technology, E-JUST, Alexandria, Egypt.

Bioinspiration & Biomimetics
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This study introduces a dynamic model and control strategy for a vine-robot, a plant-inspired growing robot. The research demonstrates precise navigation and force control in complex environments.

Keywords:
MPCgrowing robotsnonlinear controlsoft robots

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Area of Science:

  • Robotics
  • Control Systems
  • Biologically Inspired Engineering

Background:

  • Complex environments pose challenges for traditional robots.
  • Biologically inspired robots offer novel solutions for navigation and manipulation.
  • Growing robots, like the vine-robot, present unique dynamic modeling and control problems.

Purpose of the Study:

  • To develop and control a dynamic model for a plant-inspired growing robot (vine-robot).
  • To enable the vine-robot to navigate complex environments using its unique growth mechanism.
  • To regulate the robot's task space position, orientation, and interaction forces.

Main Methods:

  • Utilized the Euler-Lagrangian method for dynamic modeling.
  • Derived equations of motion for the vine-robot.
  • Employed model predictive control (MPC) for regulation tasks.

Main Results:

  • Achieved sub-millimeter precision in position control for static and time-varying trajectories.
  • Demonstrated sub-micronewton precision in force control.
  • Validated the proposed dynamic model and control strategy through simulations.

Conclusions:

  • The developed dynamic model and MPC strategy are effective for controlling the vine-robot.
  • The vine-robot shows high precision in position and force control, suitable for complex environments.
  • This research contributes to the advancement of growing robots and autonomous systems.