Robotic evaluation demonstrates stable hovering and trajectory tracking during morphological reconfiguration in multi-link quadrotors, highlighting viable real-time singularity avoidance.
Key Points
To develop a control framework and joint motion planning strategy that ensures stable hovering and accurate trajectory tracking throughout morphological changes in a reconfigurable multi-link quadrotor.
Formulated a comprehensive nonlinear dynamic model accounting for time-varying inertial properties and configuration-dependent control allocation.
Applied Dijkstra's algorithm for joint motion planning to achieve real-time singularity avoidance with an established safety margin.
Designed a proportional-integral-derivative (PID) tracking controller optimized via the Whale Optimization Algorithm (WOA), evaluated through nonlinear simulations and experimental flight tests.
Simulations and physical flight experiments confirmed stable hoverability throughout dynamic arm reconfigurations without encountering singular states.
The optimized controller maintained consistent trajectory tracking despite substantial shifts in vehicle geometry and coupled dynamics.