Efficient and reliable motion planning is essential for robots in transportation systems. Learning-based motion planners, especially those leveraging graph neural networks (GNNs), have emerged as ...

This paper proposes new motion primitives that are time optimal and feasible for a vehicle (wheeled-mobile robot). They are parameterized by a constant acceleration and a constant deceleration in an ...