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Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish
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Trajectory Tracking and Obstacle Avoidance of Robotic Fish Based on Nonlinear Model Predictive Control.

Ruilong Wang1, Ming Wang1, Yiyang Zhang1

  • 1School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, China.

Biomimetics (Basel, Switzerland)
|November 24, 2023
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Summary
This summary is machine-generated.

This study introduces a nonlinear model predictive control (NMPC) algorithm for robotic fish, enabling precise trajectory tracking and obstacle avoidance in complex underwater environments. The NMPC approach offers superior agility and resilience compared to traditional methods.

Keywords:
DWANMPCobstacle avoidancerobotic fishtrajectory tracking

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Area of Science:

  • Robotics
  • Control Systems
  • Marine Engineering

Background:

  • Accurate motion control for robotic fish in complex underwater environments remains a significant challenge.
  • Existing methods often struggle with real-time adaptation and precise maneuverability.

Purpose of the Study:

  • To propose and evaluate a nonlinear model predictive control (NMPC) algorithm for enhanced trajectory tracking and obstacle avoidance in robotic fish.
  • To demonstrate the real-time implementation and effectiveness of NMPC for agile underwater navigation.

Main Methods:

  • Formulation of a dynamic model for the robotic fish, including accelerations, within a world coordinate system.
  • Development of NMPC with obstacle avoidance and objective functions, incorporating control restrictions.
  • Comparative analysis of NMPC against Pure Pursuit (PP) for trajectory tracking and Dynamic Window Approach (DWA) for obstacle avoidance.

Main Results:

  • NMPC demonstrated superior accuracy in trajectory tracking compared to the Pure Pursuit algorithm.
  • NMPC exhibited greater resilience in obstacle avoidance planning than the Dynamic Window Approach.
  • The proposed NMPC controller effectively manages robotic fish movements with high agility.

Conclusions:

  • The NMPC-based strategy provides a viable solution for precise trajectory tracking and efficient obstacle avoidance in robotic fish.
  • This approach shows significant potential for practical application in complex underwater robotics scenarios.