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Found 5 papers, 0 papers with code
Map Prediction and Generative Entropy for Multi-Agent Exploration
By iteratively inferring interpretations of the scene throughout an exploration run, we are able to identify areas that exhibit high uncertainty in the prediction, which we formalize with the concept of generative entropy.
Deep Bayesian Future Fusion for Self-Supervised, High-Resolution, Off-Road Mapping
High-speed off-road navigation requires long-range, high-resolution maps to enable robots to safely navigate over different surfaces while avoiding dangerous obstacles.
How Does It Feel? Self-Supervised Costmap Learning for Off-Road Vehicle Traversability
Our short-scale navigation results show that using our learned costmaps leads to overall smoother navigation, and provides the robot with a more fine-grained understanding of the robot-terrain interactions.
ScoutBot: A Dialogue System for Collaborative Navigation
ScoutBot is a dialogue interface to physical and simulated robots that supports collaborative exploration of environments.
Unsupervised Semantic Scene Labeling for Streaming Data
We introduce an unsupervised semantic scene labeling approach that continuously learns and adapts semantic models discovered within a data stream.
