Tipo di tesi
Tesi di laurea magistrale
Titolo
Development in autopilot environment of a swarm robotics algorithm for hole detection in WSN
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
ARTIFICIAL INTELLIGENCE AND DATA ENGINEERING
Parole chiave
- 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
Data inizio appello
17/11/2023
Consultabilità
Non consultabile
Data di rilascio
17/11/2093
Riassunto (Italiano)
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.
