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
- Motion Planning For Autonomous Vehicles Based On Sequential Optimization.
- 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.
- Steven M Lavalle, Planning Algorithms, 2006, Cambridge University Press. Chapter 2 covers discrete planning over graphs including Dijkstra’s, A* and STRIPS etc.
