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Course Outline
Introduction to Path Planning for Autonomous Vehicles
- Path planning fundamentals and challenges.
- Applications in autonomous driving and robotics.
- Review of traditional and modern planning techniques.
Graph-Based Path Planning Algorithms
- Overview of A* and Dijkstra algorithms.
- Implementing A* for grid-based pathfinding.
- Dynamic variants: D* and D* Lite for changing environments.
Sampling-Based Path Planning Algorithms
- Random sampling techniques: RRT and RRT*.
- Path smoothing and optimization.
- Handling non-holonomic constraints.
Optimization-Based Path Planning
- Formulating the path planning problem as an optimization problem.
- Trajectory optimization using nonlinear programming.
- Gradient-based and gradient-free optimization techniques.
Learning-Based Path Planning
- Deep reinforcement learning (DRL) for path optimization.
- Integrating DRL with traditional algorithms.
- Adaptive path planning using machine learning models.
Handling Dynamic and Uncertain Environments
- Reactive planning techniques for real-time response.
- Obstacle avoidance and predictive control.
- Integrating perception data for adaptive navigation.
Evaluating and Benchmarking Path Planning Algorithms
- Metrics for path efficiency, safety, and computational complexity.
- Simulating and testing in ROS and Gazebo.
- Case study: Comparing RRT* and D* in complex scenarios.
Case Studies and Real-World Applications
- Path planning for autonomous delivery robots.
- Applications in self-driving cars and UAVs.
- Project: Implementing an adaptive path planner using RRT*.
Summary and Next Steps
Requirements
- Proficiency in Python programming.
- Experience with robotics systems and control algorithms.
- Familiarity with autonomous vehicle technologies.
Audience
- Robotics engineers specialising in autonomous systems.
- AI researchers focusing on path planning and navigation.
- Advanced-level developers working on self-driving technology.
21 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3900 € + VAT*
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