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Energy-Efficient Configuration and Control Allocation for a Dynamically Reconfigurable Underwater Robot.

Tho Dang1, Lionel Lapierre1, Rene Zapata1

  • 1Laboratory of Informatics, Robotics and MicroElectronics (LIRMM) (UMR 5506 CNRS-UM), Université Montpellier, 161 rue Ada, CEDEX 5, 34392 Montpellier, France.

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Summary

This study introduces an energy-efficient method for reconfigurable underwater robots, optimizing configuration and control for karst exploration. The approach saves energy during missions, enhancing robotic versatility and performance in challenging environments.

Keywords:
autonomous underwater robotcontrol allocationdynamically reconfigurable underwater robotoptimization

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Area of Science:

  • Robotics
  • Ocean Engineering
  • Control Systems

Background:

  • Dynamically reconfigurable underwater robots offer versatility for confined environment exploration and docking.
  • Energy efficiency is critical for long-range underwater missions, especially with reconfigurable systems.
  • Control allocation for redundant systems with input constraints is a significant challenge.

Purpose of the Study:

  • To propose an energy-efficient configuration and control allocation method for dynamically reconfigurable underwater robots.
  • To address the challenges of energy saving and control in reconfigurable robotic systems for karst exploration.
  • To optimize robot configuration and control simultaneously for enhanced mission performance.

Main Methods:

  • Sequential quadratic programming (SQP) is employed to minimize an energy-like criterion.
  • The optimization considers robotic constraints including mechanical limitations, actuator saturations, and dead zones.
  • The optimization problem is solved in real-time at each sampling instant.

Main Results:

  • Simulations for path-following and station-keeping tasks demonstrate the method's efficiency.
  • The proposed approach effectively manages energy consumption in reconfigurable underwater robots.
  • Experimental validation confirms the effectiveness of the energy-efficient configuration and control allocation.

Conclusions:

  • The developed method provides an effective solution for energy-efficient operation of dynamically reconfigurable underwater robots.
  • This approach enhances the capability of underwater robots for complex missions like karst exploration.
  • Optimized configuration and control allocation are crucial for maximizing the performance and endurance of reconfigurable robotic systems.