Browse SoTA > Computer Vision > Autonomous Vehicles > Autonomous Navigation

Autonomous Navigation

34 papers with code · Computer Vision
Subtask of Autonomous Vehicles

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 )

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Greatest papers with code

VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

CVPR 2018 charlesq34/pointnet

Accurate detection of objects in 3D point clouds is a central problem in many applications, such as autonomous navigation, housekeeping robots, and augmented/virtual reality.

3D OBJECT DETECTION AUTONOMOUS NAVIGATION FEATURE ENGINEERING OBJECT LOCALIZATION REGION PROPOSAL

DeepTraffic: Crowdsourced Hyperparameter Tuning of Deep Reinforcement Learning Systems for Multi-Agent Dense Traffic Navigation

9 Jan 2018lexfridman/deeptraffic

We present a traffic simulation named DeepTraffic where the planning systems for a subset of the vehicles are handled by a neural network as part of a model-free, off-policy reinforcement learning process.

AUTONOMOUS DRIVING AUTONOMOUS NAVIGATION Q-LEARNING

Loam_livox: A fast, robust, high-precision LiDAR odometry and mapping package for LiDARs of small FoV

15 Sep 2019hku-mars/loam_livox

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.

AUTONOMOUS NAVIGATION

Decentralized Distributed PPO: Mastering PointGoal Navigation

ICLR 2020 facebookresearch/habitat-api

We leverage this scaling to train an agent for 2. 5 Billion steps of experience (the equivalent of 80 years of human experience) -- over 6 months of GPU-time training in under 3 days of wall-clock time with 64 GPUs.

AUTONOMOUS NAVIGATION POINTGOAL NAVIGATION

DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames

ICLR 2020 facebookresearch/habitat-api

We leverage this scaling to train an agent for 2. 5 Billion steps of experience (the equivalent of 80 years of human experience) -- over 6 months of GPU-time training in under 3 days of wall-clock time with 64 GPUs.

AUTONOMOUS NAVIGATION SCENE UNDERSTANDING

An Open Source and Open Hardware Deep Learning-powered Visual Navigation Engine for Autonomous Nano-UAVs

10 May 2019pulp-platform/pulp-dronet

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.

AUTONOMOUS NAVIGATION VISUAL NAVIGATION

A 64mW DNN-based Visual Navigation Engine for Autonomous Nano-Drones

4 May 2018pulp-platform/pulp-dronet

As part of our general methodology we discuss the software mapping techniques that enable the state-of-the-art deep convolutional neural network presented in [1] to be fully executed on-board within a strict 6 fps real-time constraint with no compromise in terms of flight results, while all processing is done with only 64 mW on average.

AUTONOMOUS NAVIGATION VISUAL NAVIGATION

Learning to Navigate in Cities Without a Map

NeurIPS 2018 deepmind/streetlearn

We present an interactive navigation environment that uses Google StreetView for its photographic content and worldwide coverage, and demonstrate that our learning method allows agents to learn to navigate multiple cities and to traverse to target destinations that may be kilometres away.

AUTONOMOUS NAVIGATION

Fast and Accurate Point Cloud Registration using Trees of Gaussian Mixtures

6 Jul 2018neka-nat/probreg

Point cloud registration sits at the core of many important and challenging 3D perception problems including autonomous navigation, SLAM, object/scene recognition, and augmented reality.

AUTONOMOUS NAVIGATION POINT CLOUD REGISTRATION SCENE RECOGNITION

SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimation

24 Feb 2020lzccccc/SMOKE

Estimating 3D orientation and translation of objects is essential for infrastructure-less autonomous navigation and driving.

AUTONOMOUS NAVIGATION MONOCULAR 3D OBJECT DETECTION