Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Map-less Navigation by Leveraging Prior Demonstrations

Mark Pfeiffer
Mark Pfeiffer
Samarth Shukla
Samarth Shukla
Cesar Cadena
Cesar Cadena

international conference on robotics and automation, 2018.

Cited by: 29|Bibtex|Views40|DOI:https://doi.org/10.1109/lra.2018.2869644
EI
Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

This work presents a learning-based approach for target driven map-less navigation. The underlying navigation model is an end-to-end neural network which is trained using a combination of expert demonstrations, imitation learning (IL) and reinforcement learning (RL). While RL and IL suffer from a large sample complexity and the distributi...More

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