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Found 6 papers, 1 papers with code
SELFI: Autonomous Self-Improvement with Reinforcement Learning for Social Navigation
Specifically, SELFI stabilizes the online learning process by incorporating the same model-based learning objective from offline pre-training into the Q-values learned with online model-free reinforcement learning.
NoMaD: Goal Masked Diffusion Policies for Navigation and Exploration
In this paper, we describe how we can train a single unified diffusion policy to handle both goal-directed navigation and goal-agnostic exploration, with the latter providing the ability to search novel environments, and the former providing the ability to reach a user-specified goal once it has been located.
ViNT: A Foundation Model for Visual Navigation
In this paper, we describe the Visual Navigation Transformer (ViNT), a foundation model that aims to bring the success of general-purpose pre-trained models to vision-based robotic navigation.
SACSoN: Scalable Autonomous Control for Social Navigation
By minimizing this counterfactual perturbation, we can induce robots to behave in ways that do not alter the natural behavior of humans in the shared space.
ExAug: Robot-Conditioned Navigation Policies via Geometric Experience Augmentation
Machine learning techniques rely on large and diverse datasets for generalization.
GNM: A General Navigation Model to Drive Any Robot
Learning provides a powerful tool for vision-based navigation, but the capabilities of learning-based policies are constrained by limited training data.
