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.

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Example Common Behavior Sets

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

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Motion planning constraints

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Read more about vehicle dynamic.

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Objective functions in planning

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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.