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Found 13 papers, 2 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.
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.
Unsupervised Simultaneous Learning for Camera Re-Localization and Depth Estimation from Video
Monocular camera re-localization refers to the task of estimating the absolute camera pose from an instance image in a known environment, which has been intensively studied for alternative localization in GPS-denied environments.
Depth360: Self-supervised Learning for Monocular Depth Estimation using Learnable Camera Distortion Model
This framework is attractive for researchers because the depth and pose networks can be trained from just time sequence images without the need for the ground truth depth and poses.
Variational Monocular Depth Estimation for Reliability Prediction
Self-supervised learning for monocular depth estimation is widely investigated as an alternative to supervised learning approach, that requires a lot of ground truths.
PLG-IN: Pluggable Geometric Consistency Loss with Wasserstein Distance in Monocular Depth Estimation
We propose a novel objective for penalizing geometric inconsistencies to improve the depth and pose estimation performance of monocular camera images.
VUNet: Dynamic Scene View Synthesis for Traversability Estimation using an RGB Camera
We present VUNet, a novel view(VU) synthesis method for mobile robots in dynamic environments, and its application to the estimation of future traversability.
SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints
Whereas, the social attention component aggregates information across the different agent interactions and extracts the most important trajectory information from the surrounding neighbors.
Ranked #4 on
Trajectory Prediction
on Stanford Drone
(ADE (8/12) @K=5 metric)
GONet: A Semi-Supervised Deep Learning Approach For Traversability Estimation
We present semi-supervised deep learning approaches for traversability estimation from fisheye images.
To Go or Not To Go? A Near Unsupervised Learning Approach For Robot Navigation
It is important for robots to be able to decide whether they can go through a space or not, as they navigate through a dynamic environment.
