Path Planning and Obstacle Avoidance
( 30 Modules )

Module #1
Introduction to Path Planning and Obstacle Avoidance
Overview of the importance of path planning and obstacle avoidance in robotics and autonomous systems

Module #2
Fundamentals of Robotics and Motion Planning
Review of robotics basics, including robot types, configuration spaces, and motion planning concepts

Module #3
Types of Motion Planning
Overview of different types of motion planning, including trajectory planning, path planning, and task planning

Module #4
Path Planning Algorithms
Introduction to path planning algorithms, including graph-based, sampling-based, and optimization-based methods

Module #5
Graph-Based Path Planning
In-depth look at graph-based path planning algorithms, including Dijkstras algorithm and A* algorithm

Module #6
Sampling-Based Path Planning
In-depth look at sampling-based path planning algorithms, including PRM and RRT

Module #7
Optimization-Based Path Planning
In-depth look at optimization-based path planning algorithms, including linear and nonlinear programming

Module #8
Obstacle Avoidance Fundamentals
Overview of obstacle avoidance concepts, including sensor types and obstacle detection methods

Module #9
Sensor Types for Obstacle Avoidance
In-depth look at various sensor types used for obstacle avoidance, including lidar, radar, and vision sensors

Module #10
Obstacle Detection Methods
In-depth look at obstacle detection methods, including thresholding, edge detection, and machine learning-based approaches

Module #11
Motion Planning with Obstacles
Introduction to motion planning with obstacles, including obstacle avoidance and motion planning algorithms

Module #12
Vector Field Methods for Obstacle Avoidance
In-depth look at vector field methods for obstacle avoidance, including potential fields and velocity obstacles

Module #13
Sampling-Based Methods for Obstacle Avoidance
In-depth look at sampling-based methods for obstacle avoidance, including RRT and PRM with obstacles

Module #14
Reactive Methods for Obstacle Avoidance
In-depth look at reactive methods for obstacle avoidance, including fuzzy logic and neural networks

Module #15
Motion Planning under Uncertainty
Introduction to motion planning under uncertainty, including probabilistic motion planning and uncertainty propagation

Module #16
Motion Planning with Dynamic Obstacles
In-depth look at motion planning with dynamic obstacles, including moving obstacles and uncertain environments

Module #17
Human-Robot Interaction and Obstacle Avoidance
Introduction to human-robot interaction and obstacle avoidance, including human-aware motion planning

Module #18
Case Studies in Path Planning and Obstacle Avoidance
Real-world examples and case studies of path planning and obstacle avoidance in robotics and autonomous systems

Module #19
Advanced Topics in Path Planning and Obstacle Avoidance
Introduction to advanced topics, including multi-robot motion planning and motion planning for non-holonomic systems

Module #20
Path Planning and Obstacle Avoidance in Specific Domains
In-depth look at path planning and obstacle avoidance in specific domains, including aerial, ground, and underwater robotics

Module #21
Simulation and Visualization Tools for Path Planning and Obstacle Avoidance
Overview of simulation and visualization tools for path planning and obstacle avoidance, including Gazebo and V-REP

Module #22
Motion Planning and Obstacle Avoidance in Real-World Applications
Real-world applications of path planning and obstacle avoidance, including autonomous vehicles, robots, and drones

Module #23
Evaluating and Comparing Path Planning and Obstacle Avoidance Algorithms
Introduction to evaluating and comparing path planning and obstacle avoidance algorithms, including metrics and benchmarks

Module #24
Challenges and Limitations of Path Planning and Obstacle Avoidance
Discussion of challenges and limitations of path planning and obstacle avoidance, including computational complexity and sensor uncertainty

Module #25
Future Directions and Emerging Trends in Path Planning and Obstacle Avoidance
Overview of future directions and emerging trends in path planning and obstacle avoidance, including machine learning and swarm intelligence

Module #26
Course Wrap-Up and Final Project
Summary of key concepts and final project assignment for implementing path planning and obstacle avoidance algorithms

Module #27
Appendix A:Mathematical Preliminaries
Review of mathematical concepts relevant to path planning and obstacle avoidance, including linear algebra and probability theory

Module #28
Appendix B:Robot Operating System (ROS) Basics
Introduction to ROS and its relevance to path planning and obstacle avoidance

Module #29
Appendix C:Additional Resources and References
List of additional resources and references for further learning and research in path planning and obstacle avoidance

Module #30
Course Wrap-Up & Conclusion
Planning next steps in Path Planning and Obstacle Avoidance career

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Path Planning and Obstacle Avoidance ( 30 Modules )

Path Planning and Obstacle Avoidance
( 30 Modules )