• algorithms
• autonomous drones
• autopilot software
• drone technology
• drones
• Gazebo
• hole detection
• industrial
• JMavSim
• MAVSDK
• mission management
• multi-drone scenarios
• open-source
• PX4
• sensor deployment
• sensor deployment strategies
• simulation environment
• simulator
• swarm robotics
• swarm robotics applications

This thesis exploresinto the development of hole detection algorithms for swarm robotics, with a focus on advanced simulation environments. It explores the integration and comparative analysis of PX4 Autopilot and the JMAVSim-Gazebo combination as essential tools for evaluating and refining autonomous aerial systems. The research also introduces a novel "Localized Movement-Assisted Sensor Deployment Algorithm for Hole Detection and Healing" in the realm of wireless sensor networks. This algorithm leverages movement-assisted deployment to address the coverage hole problem and has shown superior performance in terms of accuracy, efficiency, and energy consumption. The practical implications of these domains span various real-world applications, emphasizing the importance of advanced simulation environments in technology development.

In this comprehensive investigation, i explored into the implementation of the sensor deployment algorithm, showcasing the transformative potential of autonomous drones. Real-case scenarios and simulations within the Gazebo Classic Simulator highlight the adaptability and precision of drone-based systems. The research contributes to the dynamic field of drone technology, emphasizing the role of efficient sensor deployment strategies in practical applications across industries.