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
Most implemented papers
A Graph Neural Network to Model Disruption in Human-Aware Robot Navigation
gnns4hri/sngnnv2
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This paper leverages Graph Neural Networks to model robot disruption considering the movement of the humans and the robot so that the model built can be used by path planning algorithms.
Socially Aware Motion Planning with Deep Reinforcement Learning
mit-acl/gym-collision-avoidance
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For robotic vehicles to navigate safely and efficiently in pedestrian-rich environments, it is important to model subtle human behaviors and navigation rules (e. g., passing on the right).
Intention-Net: Integrating Planning and Deep Learning for Goal-Directed Autonomous Navigation
How can a delivery robot navigate reliably to a destination in a new office building, with minimal prior information?
Correlation Flow: Robust Optical Flow Using Kernel Cross-Correlators
Robust velocity and position estimation is crucial for autonomous robot navigation.
IDD: A Dataset for Exploring Problems of Autonomous Navigation in Unconstrained Environments
prajjwal1/autonomous-object-detection
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It also reflects label distributions of road scenes significantly different from existing datasets, with most classes displaying greater within-class diversity.
An Open Source and Open Hardware Deep Learning-powered Visual Navigation Engine for Autonomous Nano-UAVs
Nano-size unmanned aerial vehicles (UAVs), with few centimeters of diameter and sub-10 Watts of total power budget, have so far been considered incapable of running sophisticated visual-based autonomous navigation software without external aid from base-stations, ad-hoc local positioning infrastructure, and powerful external computation servers.
Multi-Task Regression-based Learning for Autonomous Unmanned Aerial Vehicle Flight Control within Unstructured Outdoor Environments
brunapearson/mtrl-auto-uav
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Increased growth in the global Unmanned Aerial Vehicles (UAV) (drone) industry has expanded possibilities for fully autonomous UAV applications.
Loam_livox: A fast, robust, high-precision LiDAR odometry and mapping package for LiDARs of small FoV
LiDAR odometry and mapping (LOAM) has been playing an important role in autonomous vehicles, due to its ability to simultaneously localize the robot's pose and build high-precision, high-resolution maps of the surrounding environment.
A Little Fog for a Large Turn
code-Assasin/A_Little_fog_for_a_Large_Turn
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Small, carefully crafted perturbations called adversarial perturbations can easily fool neural networks.
Autonomous Navigation in Unknown Environments using Sparse Kernel-based Occupancy Mapping
This paper focuses on real-time occupancy mapping and collision checking onboard an autonomous robot navigating in an unknown environment.
