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Found 4 papers, 1 papers with code
Self-Supervised Traversability Prediction by Learning to Reconstruct Safe Terrain
Typically, this depends on a semantic understanding which is based on supervised learning from images annotated by a human expert.
Deep Measurement Updates for Bayes Filters
In this work, we propose the novel approach Deep Measurement Update (DMU) as a general update rule for a wide range of systems.
Learning a State Representation and Navigation in Cluttered and Dynamic Environments
We show that decoupling the pipeline into these components results in a sample efficient policy learning stage that can be fully trained in simulation in just a dozen minutes.
Learning Quadrupedal Locomotion over Challenging Terrain
The trained controller has taken two generations of quadrupedal ANYmal robots to a variety of natural environments that are beyond the reach of prior published work in legged locomotion.
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