Breakthrough in Robotics: Novel System Identification Method for Flapping-Wing Robots

Strategic Insights -

Researchers at the University of Science and Technology Beijing have introduced a novel system identification method for developing a dynamic model of flapping-wing robots, presenting a significant advancement in robotics. This method constructs an independent frame for each flapping-wing, enhancing the authenticity of the model's structure. The team proposed a parameter identification approach based on the Improved Squirrel Search Algorithm, which effectively addresses model uncertainties caused by flapping-wing motion. Experimental comparisons revealed the efficiency of this approach, and the identified model was validated through three different maneuvers.

Key Takeaways:

  • The novel system identification method emphasizes the significance of flapping-wing motion by constructing an independent frame for each flapping-wing.
  • The Improved Squirrel Search Algorithm is proposed for parameter identification, effectively addressing model uncertainties caused by flapping-wing motion.
  • Experimental comparisons revealed the efficiency of this approach in parameter identification.
  • The identified model was validated through three different maneuvers, demonstrating its adaptability.
  • This research provides valuable insights and foundations for future FWR control studies.
  • The University of Science and Technology Beijing's Key Laboratory of Intelligent Bionic Unmanned Systems, Ministry of Education, collaborated on this research.
  • Additional authors include Wei He, Tingting Meng, Xiuyu He, and Qiang Fu.
  • The publisher of the journal ISA Transactions is Elsevier Science Inc.

Statistics:

  • 3 different maneuvers were selected to test the adaptability of the identified model.
  • The Improved Squirrel Search Algorithm was used for parameter identification.
  • Experimental comparisons revealed the efficiency of this approach in parameter identification, demonstrating its potential for future FWR control studies.
  • The research provided valuable insights and foundations for future FWR control studies.
  • The University of Science and Technology Beijing's Key Laboratory of Intelligent Bionic Unmanned Systems, Ministry of Education, collaborated on this research.
  • Additional authors include Wei He, Tingting Meng, Xiuyu He, and Qiang Fu.

Sources:

  • Model identification for a flapping-wing robot based on improved squirrel search algorithm. ISA Transactions, 2025.
  • NewsRx. Researchers at University of Science and Technology Beijing Target Robotics (Model identification for a flapping-wing robot based on improved squirrel search algorithm). Journal of Engineering. October 27, 2025; p 3550.