164-12-Motion-Planing-Problem

Mission, scenarios and behaviors

Task: Navigate the robot itself from the current position to final destination on the map, without human intervention.

Goal: find most efficient path (trajectory) in terms of time or distance travelled.

Example Common Behavior Sets

• Speed tracking
• Deceleration to stop
• Stay stopped
• Yield
• Emergency stop

Motion planning constraints

Read more about vehicle dynamic.

Objective functions in planning

Supplementary Readings

1. Motion Planning For Autonomous Vehicles Based On Sequential Optimization.
2. The kinematic bicycle model: A consistent model for planning feasible trajectories for autonomous vehicles, 2017 IEEE Intelligent Vehicles Symposium (IV), 2017. Gives an overview of the kinematic bicycle model.
3. Steven M Lavalle, Planning Algorithms, 2006, Cambridge University Press. Chapter 2 covers discrete planning over graphs including Dijkstra’s, A* and STRIPS etc.