Autonomous Navigation
130 papers with code • 0 benchmarks • 5 datasets
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 )
Benchmarks
These leaderboards are used to track progress in Autonomous Navigation
RELLIS-3D
JRDB
IN2LAAMA
Latest papers with no code
Prepared for the Worst: A Learning-Based Adversarial Attack for Resilience Analysis of the ICP Algorithm
This paper presents a novel method to assess the resilience of the Iterative Closest Point (ICP) algorithm via deep-learning-based attacks on lidar point clouds.
Improved LiDAR Odometry and Mapping using Deep Semantic Segmentation and Novel Outliers Detection
In this work, we propose a novel framework for real-time LiDAR odometry and mapping based on LOAM architecture for fast moving platforms.
UFO: Uncertainty-aware LiDAR-image Fusion for Off-road Semantic Terrain Map Estimation
Autonomous off-road navigation requires an accurate semantic understanding of the environment, often converted into a bird's-eye view (BEV) representation for various downstream tasks.
Map-aided annotation for pole base detection
In the absence of height information, the map features are represented as pole bases at the ground level.
RoadRunner - Learning Traversability Estimation for Autonomous Off-road Driving
Furthermore, RoadRunner improves the system latency by a factor of roughly 4, from 500 ms to 140 ms, while improving the accuracy for traversability costs and elevation map predictions.
Self-Supervised Interpretable Sensorimotor Learning via Latent Functional Modularity
We further delve into the interpretability of our network through the post-hoc analysis of perceptual saliency maps and latent decision vectors.
3D Gaussian as a New Vision Era: A Survey
3D Gaussian Splatting (3D-GS) has emerged as a significant advancement in the field of Computer Graphics, offering explicit scene representation and novel view synthesis without the reliance on neural networks, such as Neural Radiance Fields (NeRF).
Hybridnet for depth estimation and semantic segmentation
Semantic segmentation and depth estimation are two important tasks in the area of image processing.
Haris: an Advanced Autonomous Mobile Robot for Smart Parking Assistance
This paper presents Haris, an advanced autonomous mobile robot system for tracking the location of vehicles in crowded car parks using license plate recognition.
Data-Driven Strategies for Coping with Incomplete DVL Measurements
Autonomous underwater vehicles are specialized platforms engineered for deep underwater operations.
