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Visual Memory for Robust Path Following
Ashish Kumar · Saurabh Gupta · David Fouhey · Sergey Levine · Jitendra Malik

Wed Dec 05 07:05 AM -- 07:20 AM (PST) @ Room 220 E

Humans routinely retrace a path in a novel environment both forwards and backwards despite uncertainty in their motion. In this paper, we present an approach for doing so. Given a demonstration of a path, a first network generates an abstraction of the path. Equipped with this abstraction, a second network then observes the world and decides how to act in order to retrace the path under noisy actuation and a changing environment. The two networks are optimized end-to-end at training time. We evaluate the method in two realistic simulators, performing path following both forwards and backwards. Our experiments show that our approach outperforms both a classical approach to solving this task as well as a number of other baselines.

Author Information

Ashish Kumar (UC Berkeley)
Saurabh Gupta (UC Berkeley / FAIR / UIUC)
David Fouhey (UC Berkeley)
Sergey Levine (UC Berkeley)
Jitendra Malik (University of California at Berkley)

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