Visual Navigation
105 papers with code • 6 benchmarks • 16 datasets
Visual Navigation is the problem of navigating an agent, e.g. a mobile robot, in an environment using camera input only. The agent is given a target image (an image it will see from the target position), and its goal is to move from its current position to the target by applying a sequence of actions, based on the camera observations only.
Source: Vision-based Navigation Using Deep Reinforcement Learning
Benchmarks
These leaderboards are used to track progress in Visual Navigation
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Libraries
Use these libraries to find Visual Navigation models and implementations
Replica
AI2-THOR
SUNCG
R2R
2D-3D-S
AVD
HELP
MINOS
House3D Environment
Talk the Walk
Latest papers with no code
Feudal Networks for Visual Navigation
We introduce a new approach to visual navigation using feudal learning, which employs a hierarchical structure consisting of a worker agent, a mid-level manager, and a high-level manager.
Value Explicit Pretraining for Learning Transferable Representations
We propose Value Explicit Pretraining (VEP), a method that learns generalizable representations for transfer reinforcement learning.
ReCoRe: Regularized Contrastive Representation Learning of World Model
To address these challenges, we present a world model that learns invariant features using (i) contrastive unsupervised learning and (ii) an intervention-invariant regularizer.
Building Category Graphs Representation with Spatial and Temporal Attention for Visual Navigation
To this end, an agent needs to 1) learn a piece of certain knowledge about the relations of object categories in the world during training and 2) look for the target object based on the pre-learned object category relations and its moving trajectory in the current unseen environment.
Visual Hindsight Self-Imitation Learning for Interactive Navigation
Interactive visual navigation tasks, which involve following instructions to reach and interact with specific targets, are challenging not only because successful experiences are very rare but also because the complex visual inputs require a substantial number of samples.
Deep Learning for Visual Navigation of Underwater Robots
The scope of this paper includes the visual perception of underwater robotics with deep learning methods, the available visual underwater datasets, imitation learning, and reinforcement learning methods for navigation.
Bird's Eye View Based Pretrained World model for Visual Navigation
We trained the model using data from a Differential drive robot in the CARLA simulator.
Invariance is Key to Generalization: Examining the Role of Representation in Sim-to-Real Transfer for Visual Navigation
The data-driven approach to robot control has been gathering pace rapidly, yet generalization to unseen task domains remains a critical challenge.
Multimodal Large Language Model for Visual Navigation
Recent efforts to enable visual navigation using large language models have mainly focused on developing complex prompt systems.
A Decentralized Cooperative Navigation Approach for Visual Homing Networks
Visual homing is a lightweight approach to visual navigation.
