Papers Visual Navigation
“Visual Navigation” 태그가 달린 논문 434편 · 필터 해제
NavArena: Automated Construction of Goal-Oriented Navigation Benchmarks from 3D Gaussian Splatting Reconstructions
Fixed 3D Gaussian Splatting (3DGS) reconstructions provide realistic novel views but lack the traversability constraints, valid goals, and closed-loop protocols required for navigation evaluation. We introduce NavArena, …
Visual NavigationCanonNav: Disentangling Navigation Behavior from Camera Geometry in Cross-Platform Visual Navigation
While visual navigation has advanced through imitation learning from cross-platform demonstrations, fully leveraging such data remains challenging. First, directly learning from image-trajectory pairs entangles navigatio…
Visual NavigationReinforced Planning with Latent World Models
Humans solve complex problems by constructing plans and mentally simulating their outcomes with an internal model of the world. Machine learning has produced world models that similarly predict the outcomes of action seq…
Visual NavigationDevGRU: Depth-guided Visual Navigation using a Collision-aware Recurrent Model
Existing visual navigation models often aim to develop foundation models that can generalize robot navigation across diverse platforms. However, many of these models are prone to collisions when deployed in complex indoo…
Visual NavigationRobot NavigationPose EstimationUniNav: A Unified World-Action Diffusion Model for Visual Navigation
Image-goal visual navigation is a fundamental capability for embodied agents. Existing navigation policies efficiently predict waypoint trajectories but lack visual foresight, while navigation world models can anticipate…
Trajectory PredictionVisual NavigationX-NavDP: Generalizing Navigation Diffusion Policy to Novel Behavior and Embodiments with Group Q-score Reweighted Matching
Pretraining navigation diffusion policies rely on large-scale expert demonstrations. These data are typically generated by a fully-informed oracle planner suited to a single nominal robot. This limits the policy's genera…
Reinforcement LearningVisual NavigationVoLN: Vision-Only Long-Horizon Navigation---Paradigm, Benchmark, and Method
Vision-and-Language Navigation (VLN) enables embodied agents to follow natural-language instructions. However, route-level instructions commonly encode spatial priors, such as orientation, distance, and layout, that are …
Visual NavigationEA-Nav: Learning Safe Visual Navigation Policies with Embodiment Awareness
Cross-embodiment navigation is a key challenge in embodied intelligence. Due to differences in embodiment, the same visual observation may imply different actions for different agents, making prediction ambiguous when re…
Reinforcement LearningVisual NavigationDifference-Based Relational Learning for Zero-Shot Object-Goal Visual Navigation With Direct Sim-to-Real Transfer
End-to-end deep reinforcement learning (DRL) for zero-shot object-goal visual navigation remains challenged by the sim-to-real gap, particularly variations in object appearance and restricted camera field-of-view (FoV). …
Zero-shot GeneralizationReinforcement LearningVisual NavigationNavCMPO: Critic-Guided MeanFlow Policy Optimization for Adaptive Navigation
End-to-end diffusion-based policies have demonstrated strong performance in mapless visual navigation, but their iterative denoising process introduces substantial inference latency, while behavior cloning limits perform…
Reinforcement LearningVisual NavigationPixelLoop: Shortcut Topological Navigation with Pixel-Level Loops
Although topological mapping and navigation have been studied extensively, the specific role and downstream effect of loop closures in purely topological representations has received relatively little attention. Importan…
Visual NavigationEnabling 24-hour Agricultural Robotics: Unsupervised Day-to-Night Cross-Modal Image Translation for Nighttime Visual Navigation
While visual navigation has been extensively studied in agricultural robotics, most existing systems assume daytime conditions. In fact, deploying autonomous robots at night offers significant advantages, including 24-ho…
Semantic SegmentationVisual NavigationLearning to Navigate Efficiently with Only 0.58M Trainable Parameters
Recent progress in visual navigation has largely been driven by scale: end-to-end policies with hundreds of millions of parameters trained on billions of frames or large-scale simulated data. We ask how much of this scal…
Visual NavigationSocial-spatial dependencies for learning visual navigation
Navigation for social organisms rarely is a fully independent activity. Group structure and dynamics, as well as embodied interactions, critically influence useful behavior. Individual neural network controlled agents ar…
Collision AvoidanceVisual NavigationGemNav: Discrete-Token Visual Robot Navigation using a Multimodal Large Language Model
Visual navigation policies built on large pretrained models have so far followed a common recipe: a dedicated visual encoder, a bespoke action head, and training on thousands of hours of cross-embodiment datasets. We ask…
Visual NavigationRobot NavigationLH-AVLN: A Benchmark for Long-Horizon Audio-Visual-Language Navigation
Embodied navigation is moving toward long-horizon missions, yet existing long-horizon benchmarks are largely acoustically silent, and audio-visual navigation tasks typically focus on a single goal. We introduce LH-AVLN, …
Visual NavigationACID: Action Consistency via Inverse Dynamics for Planning with World Models
Decision-time planning with action-conditioned world models has become a popular paradigm for embodied control. However, the standard planning cost judges a candidate solely by how close its predicted terminal state lies…
Visual NavigationBIFROST: Bridging Invariant Feature Representation for Observation-space Sim2Real Transfer
Sim2real transfer for robot policy learning suffers due to mismatch between simulation and reality. Existing methods typically address each gap in isolation through separate adaptation modules, which are composed or laye…
Domain AdaptationVisual NavigationLeCropFollow: Latent Space Planning for Navigation in Unstructured Crop Fields
Unstructured navigational features, such as irregular planting or discontinuities, remain the primary failure mode for under-canopy agricultural robots. Existing geometric approaches often fail in these scenarios because…
Reinforcement LearningVisual NavigationPondering the Way: Spatial-perceiving World Action Model for Embodied Navigation
Existing world model-based planners for visual navigation typically follow a verification-centric paradigm, decoupling goal intent from trajectory synthesis. This approach suffers from candidate dependence, heavy computa…
Zero-shot GeneralizationVisual Navigation