Learning Path

Configuration Space → Trajectory Optimization

This learning path guides robotics students through the fundamental concepts and algorithms of robot path planning. Starting with configuration spaces and graph search, it progresses to sampling-based methods and potential fields, and concludes with path smoothing techniques. The path emphasizes the geometric intuition and algorithmic trade-offs essential for effective path planning in robotics.