Robot Navigation
130 papers with code • 4 benchmarks • 14 datasets
The fundamental objective of mobile Robot Navigation is to arrive at a goal position without collision. The mobile robot is supposed to be aware of obstacles and move freely in different working scenarios.
Benchmarks
These leaderboards are used to track progress in Robot Navigation
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Libraries
Use these libraries to find Robot Navigation models and implementationsDatasets
TAO
Gibson Environment
Habitat Platform
QDax
ISOD
Latest papers
SG-PGM: Partial Graph Matching Network with Semantic Geometric Fusion for 3D Scene Graph Alignment and Its Downstream Tasks
dfki-av/sg-pgm
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The alignment between 3D scene graphs is the first step of many downstream tasks such as scene graph aided point cloud registration, mosaicking, overlap checking, and robot navigation.
Belief Aided Navigation using Bayesian Reinforcement Learning for Avoiding Humans in Blind Spots
JinnnK/BNBRLplus
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Recent research on mobile robot navigation has focused on socially aware navigation in crowded environments.
TTA-Nav: Test-time Adaptive Reconstruction for Point-Goal Navigation under Visual Corruptions
maytusp/tta-nav
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Our "plug-and-play" method incorporates a top-down decoder to a pre-trained navigation model.
Transformable Gaussian Reward Function for Socially-Aware Navigation with Deep Reinforcement Learning
jinnnk/tgrf
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Although reinforcement learning technique has fostered the advancement of socially aware navigation, defining appropriate reward functions, especially in congested environments, has posed a significant challenge.
SemanticSLAM: Learning based Semantic Map Construction and Robust Camera Localization
leomingyangli/semanticslam
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This approach enables the creation of a semantic map of the environment and ensures reliable camera localization.
STIGCN: spatial–temporal interaction‑aware graph convolution network for pedestrian trajectory prediction
Chenwangxing/STIGCN_master
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The Journal of Supercomputing 2023
STIGCN considers the correlation between social interaction and pedestrian movement factors to achieve more accurate interaction modeling.
OVIR-3D: Open-Vocabulary 3D Instance Retrieval Without Training on 3D Data
This work presents OVIR-3D, a straightforward yet effective method for open-vocabulary 3D object instance retrieval without using any 3D data for training.
Variational Curriculum Reinforcement Learning for Unsupervised Discovery of Skills
seongun-kim/vcrl
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We validate the effectiveness of our approach on complex navigation and robotic manipulation tasks in terms of sample efficiency and state coverage speed.
Think, Act, and Ask: Open-World Interactive Personalized Robot Navigation
To address these limitations, we introduce Zero-shot Interactive Personalized Object Navigation (ZIPON), where robots need to navigate to personalized goal objects while engaging in conversations with users.
Robots That Can See: Leveraging Human Pose for Trajectory Prediction
google-research/human-scene-transformer
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Anticipating the motion of all humans in dynamic environments such as homes and offices is critical to enable safe and effective robot navigation.
