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Modeling of Cooperative Robotic Systems and Predictive Control Applied to Biped Robots and UAV-UGV Docking with Task

Baris Taner1, Kamesh Subbarao1

  • 1Department of Mechanical and Aerospace Engineering, The University of Texas at Arlington, 500 W. First St., Arlington, TX 76019, USA.

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|May 25, 2024
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Summary

This study introduces a cooperative modeling framework and fast-slow model predictive control for complex multi-agent systems. The approach simplifies control and enables prioritized docking maneuvers for robots and vehicles.

Keywords:
cooperationdockingmodel predictive controlquadcopterrover

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Area of Science:

  • Robotics
  • Control Systems Engineering
  • Complex Systems Modeling

Background:

  • Complex systems like multi-robot teams require sophisticated control strategies.
  • Deriving governing dynamical equations for multi-body systems is computationally intensive.
  • Cooperative control is essential for coordinated tasks such as docking.

Purpose of the Study:

  • To develop a cooperative modeling framework to simplify the derivation of dynamical equations for complex multi-body systems.
  • To enable optimization-based trajectory generation for cooperative systems.
  • To implement a fast-slow model predictive control (MPC) strategy with task prioritization for cooperative docking maneuvers.

Main Methods:

  • A cooperative modeling framework is proposed to reduce complexity in deriving dynamical equations.
  • An optimization-based trajectory generation method is utilized for complex systems.
  • A fast-slow MPC strategy combines non-linear and linear MPC formulations, employing Euler discretization for direct transcription and close-proximity motion control.

Main Results:

  • The framework successfully simplifies the modeling of complex multi-agent systems.
  • The fast-slow MPC strategy effectively manages prioritized docking maneuvers.
  • Demonstrated successful trajectory generation and modeling on a biped robot and a quadcopter docking with a rover.

Conclusions:

  • The cooperative modeling framework enhances the tractability of complex system dynamics.
  • The prioritized fast-slow MPC strategy provides an efficient solution for cooperative docking tasks.
  • The proposed methods are validated through simulations and a case study involving a quadcopter and a rover.