Indoor Mapping Guidance Algorithm of Rotary-Wing UAV Including Dead-End Situations.

Area of Science:

• Robotics
• Artificial Intelligence
• Autonomous Systems

Background:

• Quadrotors are increasingly used for indoor mapping.
• Autonomous navigation in unknown environments presents significant challenges, including sensor limitations and obstacle avoidance.
• Existing mapping algorithms often struggle with dynamic environments and dead-end scenarios.

Purpose of the Study:

• To propose a robust mapping guidance algorithm for quadrotors operating in unknown indoor environments.
• To enhance the autonomy and efficiency of quadrotor-based indoor mapping.
• To develop a system capable of overcoming navigation challenges like dead-ends.

Main Methods:

• A quadrotor equipped with a limited-range sensor collects object data points.
• The algorithm computes velocity and yaw commands for safe obstacle traversal and collision prevention.
• The distance transform method is utilized for dead-end and exploration completion logic.
• A specialized maneuver is implemented to escape dead-ends and discover new areas.

Main Results:

• The proposed algorithm enables the quadrotor to move around objects while maintaining a safe distance.
• Collision avoidance is achieved through velocity vector control.
• The distance transform method effectively identifies dead-end situations and exploration completion.
• The implemented maneuver successfully allows the quadrotor to escape dead-ends and resume mapping.

Conclusions:

• The developed mapping guidance algorithm significantly improves quadrotor navigation in unknown indoor environments.
• The algorithm demonstrates effectiveness in handling complex scenarios, including dead-ends, through intelligent maneuvers.
• Numerical simulations validate the performance and reliability of the proposed system for autonomous mapping.