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This study presents a novel adaptive control scheme for nonholonomic mobile robots, enabling precise trajectory tracking and obstacle avoidance under complex velocity constraints. The method ensures safety and performance through dynamic constraint adaptation.

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Area of Science:

  • Robotics
  • Control Systems Engineering

Background:

  • Nonholonomic mobile robots face challenges in trajectory tracking and obstacle avoidance due to inherent motion constraints.
  • Existing control methods often struggle to simultaneously manage multiple, complex velocity constraints and performance specifications.

Purpose of the Study:

  • To develop an adaptive control scheme for nonholonomic mobile robots that addresses trajectory/target-tracking and obstacle-avoidance.
  • To ensure compliance with diamond-shaped velocity constraints and predefined output performance specifications.
  • To enhance robot safety and navigation capabilities in dynamic environments.

Main Methods:

  • Leveraging adaptive performance control to dynamically adjust output performance specifications.
  • Integrating multiple constraints into a single adaptive performance function with a simple adaptive law.
  • Introducing a robust velocity estimator to reconstruct unmeasured trajectory/target velocities.

Main Results:

  • The proposed scheme successfully manages trajectory-tracking and obstacle-avoidance under diamond-shaped velocity constraints.
  • Adaptive performance control dynamically adjusts specifications, ensuring constraint compliance and safety.
  • The robust velocity estimator accurately reconstructs velocities, improving control precision.

Conclusions:

  • The developed adaptive control scheme is effective and robust for nonholonomic mobile robot navigation.
  • The integration of adaptive performance control offers a unified approach to managing complex constraints.
  • Validation through simulations and real-world experiments confirms the practical applicability of the method.