Published on Fri May 31 2019

Graduated Fidelity Lattices for Motion Planning under Uncertainty

Adrián González-Sieira, Manuel Mucientes, Alberto Bugarín

The probability of collision is reliably estimated considering the robot shape. The fidelity adapts to the complexity of the environment. Safe and optimal paths are found with an informed search algorithm.

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Abstract

We present a novel approach for motion planning in mobile robotics under sensing and motion uncertainty based on state lattices with graduated fidelity. The probability of collision is reliably estimated considering the robot shape, and the fidelity adapts to the complexity of the environment, improving the planning efficiency while maintaining the performance. Safe and optimal paths are found with an informed search algorithm, for which a novel multi-resolution heuristic is presented. Results for different scenarios and robot shapes are given, showing the validity of the proposed methods.