SOTAVerified

Autonomous Navigation

Autonomous navigation is the task of autonomously navigating a vehicle or robot to or around a location without human guidance.

( Image credit: Approximate LSTMs for Time-Constrained Inference: Enabling Fast Reaction in Self-Driving Cars )

Papers

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Showing 451–500 of 589 papers

TitleStatusHype
Autonomously Navigating a Surgical Tool Inside the Eye by Learning from Demonstration—0
Autonomous Navigation and Configuration of Integrated Access Backhauling for UAV Base Station Using Reinforcement Learning—0
Autonomous navigation for low-altitude UAVs in urban areas—0
Autonomous Navigation for Quadrupedal Robots with Optimized Jumping through Constrained Obstacles—0
Autonomous Navigation in Complex Environments—0
Autonomous Navigation in Dynamic Environments: Deep Learning-Based Approach—0
Autonomous Navigation of an Ultrasound Probe Towards Standard Scan Planes with Deep Reinforcement Learning—0
Autonomous navigation of catheters and guidewires in mechanical thrombectomy using inverse reinforcement learning—0
Autonomous Navigation of Tractor-Trailer Vehicles through Roundabout Intersections—0
Autonomous Navigation through intersections with Graph ConvolutionalNetworks and Conditional Imitation Learning for Self-driving Cars—0
Autonomous Off-road Navigation over Extreme Terrains with Perceptually-challenging Conditions—0
Autonomous Systems: Autonomous Systems: Indoor Drone Navigation—0
Avoidance of Manual Labeling in Robotic Autonomous Navigation Through Multi-Sensory Semi-Supervised Learning—0
BadODD: Bangladeshi Autonomous Driving Object Detection Dataset—0
Bayesian Incremental Inference Update by Re-using Calculations from Belief Space Planning: A New Paradigm—0
Beyond Segmentation: Road Network Generation with Multi-Modal LLMs—0
Boosting Image Super-Resolution Via Fusion of Complementary Information Captured by Multi-Modal Sensors—0
Bridging Model-based Safety and Model-free Reinforcement Learning through System Identification of Low Dimensional Linear Models—0
Bringing Background into the Foreground: Making All Classes Equal in Weakly-supervised Video Semantic Segmentation—0
Building3D: An Urban-Scale Dataset and Benchmarks for Learning Roof Structures from Point Clouds—0
Building3D: A Urban-Scale Dataset and Benchmarks for Learning Roof Structures from Point Clouds—0
Building Intelligent Autonomous Navigation Agents—0
Camera-Only Bird's Eye View Perception: A Neural Approach to LiDAR-Free Environmental Mapping for Autonomous Vehicles—0
Can Reasons Help Improve Pedestrian Intent Estimation? A Cross-Modal Approach—0
Can You Trust Your Pose? Confidence Estimation in Visual Localization—0
Capsule Network Performance with Autonomous Navigation—0
CleanMAP: Distilling Multimodal LLMs for Confidence-Driven Crowdsourced HD Map Updates—0
Collection: Datasets from AFAR Challenge—0
Comparison of Deep Space Navigation Using Optical Imaging, Pulsar Time-of-Arrival Tracking, and/or Radiometric Tracking—0
Computational complexity reduction of deep neural networks—0
Connecting Visual Experiences using Max-flow Network with Application to Visual Localization—0
Context-aware 6D Pose Estimation of Known Objects using RGB-D data—0
Context-Conditional Navigation with a Learning-Based Terrain- and Robot-Aware Dynamics Model—0
Contrast & Compress: Learning Lightweight Embeddings for Short Trajectories—0
Convergence of Communications, Control, and Machine Learning for Secure and Autonomous Vehicle Navigation—0
CoverNav: Cover Following Navigation Planning in Unstructured Outdoor Environment with Deep Reinforcement Learning—0
Cross-Modal Knowledge Transfer Without Task-Relevant Source Data—0
CSAOT: Cooperative Multi-Agent System for Active Object Tracking—0
Cyber-resilience for marine navigation by information fusion and change detection—0
DAE-Fuse: An Adaptive Discriminative Autoencoder for Multi-Modality Image Fusion—0
Data-Driven Meets Navigation: Concepts, Models, and Experimental Validation—0
Data-Driven Strategies for Coping with Incomplete DVL Measurements—0
Decomposing the Prediction Problem; Autonomous Navigation by neoRL Agents—0
Deep Convolutional Neural Network-Based Autonomous Drone Navigation—0
Deep Global-Relative Networks for End-to-End 6-DoF Visual Localization and Odometry—0
Deep Learning-Based Multi-Modal Fusion for Robust Robot Perception and Navigation—0
Deep Learning Computer Vision Algorithms for Real-time UAVs On-board Camera Image Processing—0
Deep Neural Network for Real-Time Autonomous Indoor Navigation—0
DeepPoint: A Deep Learning Model for 3D Reconstruction in Point Clouds via mmWave Radar—0
Deep Reinforcement Learning for Time Optimal Velocity Control using Prior Knowledge—0
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