Integrating metric and semantic maps for vision-only automated parking | IEEE Conference Publication | IEEE Xplore

Integrating metric and semantic maps for vision-only automated parking


Abstract:

We present a framework for integrating two layers of map which are often required for fully automated operation: metric and semantic. Metric maps are likely to improve wi...Show More

Abstract:

We present a framework for integrating two layers of map which are often required for fully automated operation: metric and semantic. Metric maps are likely to improve with subsequent visitations to the same place, while semantic maps can comprise both permanent and fluctuating features of the environment. However, it is not clear from the state of the art how to update the semantic layer as the metric map evolves. The strengths of our method are threefold: the framework allows for the unsupervised evolution of both maps as the environment is revisited by the robot; it uses vision-only sensors, making it appropriate for production cars; and the human labelling effort is minimised as far as possible while maintaining high fidelity. We evaluate this on two different car parks with a fully automated car, performing repeated automated parking manoeuvres to demonstrate the robustness of the system.
Date of Conference: 26-30 May 2015
Date Added to IEEE Xplore: 02 July 2015
ISBN Information:
Print ISSN: 1050-4729
Conference Location: Seattle, WA, USA

References

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