Development of a Collision Avoidance System Using Multiple Distance Sensors for Indoor Inspection Drone

Drones, particularly those designed for indoor inspections, are widely used across various industries for tasks such as infrastructure monitoring, maintenance, and security. This study focuses on developing a robust collision avoidance system for teleoperated indoor drones, ensuring comprehensive 360-degree horizontal safety during flight. By integrating multiple cost-effective and compact Time-of-Flight (ToF) distance sensors, the system enhances real-time obstacle detection and collision prevention. A custom sensor module, strategically installed on the drone, facilitates continuous environmental monitoring and dynamic flight adjustment. This module continuously provides real-time distance data to the collision avoidance algorithm. Additionally, the system receives user control signals from the remote operator, which are then transmitted to the flight controller. Upon detecting an obstacle, the system immediately modifies these control signals to adjust the drone’s motion, thereby avoiding collisions and ensuring the safety of both the drone and its surroundings. The methodology involves initializing and calibrating multiple sensors, collecting and processing ranging data, and dynamically adjusting motion commands based on proximity alerts. This approach significantly improves the safety and operational efficiency of drones in complex indoor environments.