Example: ML Planning

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Background

The ml-planning example demonstrates how a learning-based planning component can be integrated alongside the classical OpenADStack planning pipeline. It focuses on comparing and switching between different trajectory generation modes during a running simulation.

This example covers:

• parallel execution of a classical planner and an ML-based reference trajectory generator

• orchestration logic for switching between planning modes

• additional sensor inputs required by ML-based planning components