Unmanned Aerial Vehicles (UAVs) are increasingly important in modern applications, but their fixed design limits their adaptability in variable environments. In response to this challenge, this paper proposes a multi-modal transformable robot designed to achieve efficient task execution in complex environments. With innovative design of the airframe structure, the robot can dynamically adapt to a variety of modalities, including flying, rolling, and crawling, through 16 actuators and 22 degrees of freedom, significantly enhancing its mobility in unstructured environments. This paper provides a detailed exposition of the robot’s design principles, kinematic analysis, dynamic modeling, and establishes a simulation system using a PID control algorithm to verify the model’s predictive and control capabilities. The simulation results demonstrate the robot’s superior performance in flight trajectory, attitude control, velocity, and angular acceleration changes. This study is not only innovative in theory but also shows good performance and broad application prospects in practical applications, providing a new direction for the development of future UAV technology.

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Modeling and Simulation of Multi-Modal Transformable Land-Air Robots

  • Xunfei Yu,
  • Xianlong Ma,
  • Weijun Hu,
  • Ruichang Wang

摘要

Unmanned Aerial Vehicles (UAVs) are increasingly important in modern applications, but their fixed design limits their adaptability in variable environments. In response to this challenge, this paper proposes a multi-modal transformable robot designed to achieve efficient task execution in complex environments. With innovative design of the airframe structure, the robot can dynamically adapt to a variety of modalities, including flying, rolling, and crawling, through 16 actuators and 22 degrees of freedom, significantly enhancing its mobility in unstructured environments. This paper provides a detailed exposition of the robot’s design principles, kinematic analysis, dynamic modeling, and establishes a simulation system using a PID control algorithm to verify the model’s predictive and control capabilities. The simulation results demonstrate the robot’s superior performance in flight trajectory, attitude control, velocity, and angular acceleration changes. This study is not only innovative in theory but also shows good performance and broad application prospects in practical applications, providing a new direction for the development of future UAV technology.