Artificial intelligence (AI) is an essential component of modern aerial robotics, enabling drones to perform a wide range of tasks with greater efficiency, accuracy, and autonomy. AI algorithms are used to control the flight of the drone, to process data collected by its sensors, and to make decisions based on that data.
Some of the AI techniques used in aerial robotics include:
- Computer vision: This involves using cameras and other sensors to capture visual data, which can be analyzed by AI algorithms to detect objects, track movement, and identify patterns.
- Machine learning: This involves training AI algorithms to recognize specific patterns or behaviors, based on large amounts of data. For example, a drone could be trained to identify different types of terrain, or to recognize patterns of activity that might indicate the presence of a threat.
- Deep learning: This is a subset of machine learning that involves using neural networks to learn complex patterns and relationships in data. Deep learning is particularly useful for tasks such as object detection, where the algorithm needs to identify specific features of an object in order to classify it correctly.
- Reinforcement learning: This involves training an AI algorithm to make decisions based on feedback it receives from its environment. For example, a drone could be trained to fly a specific route while avoiding obstacles and minimizing energy consumption.
AI algorithms can also be used to coordinate multiple drones, allowing them to work together to achieve a common goal. For example, a swarm of drones could be used to search for missing persons or to inspect a large area for damage.
Special Session Chairs
- Israel Cruz Vega
icruzv@inaoep.mx
National Institute of Astrophysics, Optics and Electronics (INAOE), Mexico - José MartÃnez Carranza
carranza@inaoep.mx
National Institute of Astrophysics, Optics and Electronics (INAOE), Mexico