Visão Geral
Este Curso Sistemas autônomos, apresenta os fundamentos técnicos e arquiteturais dos sistemas autônomos, abordando como softwares e hardwares são projetados para perceber o ambiente, tomar decisões e agir de forma independente. O foco está em conceitos como percepção, planejamento, controle, aprendizado de máquina, integração de sensores e confiabilidade, aplicáveis a veículos autônomos, robótica, drones, sistemas industriais e agentes inteligentes.
Conteúdo Programatico
Module 1: Introduction to Autonomous Systems
- Definition and Characteristics of Autonomous Systems
- Levels of Autonomy
- Applications and Industry Use Cases
Module 2: System Architecture for Autonomy
- Hardware and Software Architectures
- Sense-Plan-Act Loop
- Real-Time and Distributed Systems
Module 3: Sensors and Actuators
- Cameras, LiDAR, Radar, and IMU
- Actuators and Control Interfaces
- Sensor Calibration
Module 4: Perception and Sensor Fusion
- Computer Vision Fundamentals
- Localization and Mapping
- Sensor Fusion Techniques
Module 5: Decision Making and Planning
- State Estimation
- Path Planning Algorithms
- Behavior Planning
Module 6: Control Systems
- Feedback and Control Loops
- PID and Model-Based Control
- Trajectory Tracking
Module 7: Machine Learning for Autonomous Systems
- Supervised and Reinforcement Learning
- Learning-Based Perception
- Simulation and Data Generation
Module 8: Safety, Reliability, and Validation
- Functional Safety Concepts
- Fault Detection and Recovery
- Testing and Simulation
Module 9: Ethics, Regulation, and Security
- Ethical Considerations
- Regulatory Landscape
- Cybersecurity for Autonomous Systems
Module 10: Capstone Project
- Designing an Autonomous System
- Simulation and Evaluation
- System Analysis and Presentation