sensor fusion related contents

aau-cns / mars_lib

sensor fusion, MaRS: A Modular and Robust Sensor-Fusion Framework

From organization aau-cns

adafruit / adafruit_sensorlab

sensor fusion, Arduino library for scientific sensor readings/fusions/manipulations

From organization adafruit

alalagong / sensorfusionwork

sensor fusion, 多传感器融合课程作业代码

From user alalagong

aleksandrkim61 / eagermot

sensor fusion, Official code for "EagerMOT: 3D Multi-Object Tracking via Sensor Fusion" [ICRA 2021]

From user aleksandrkim61

autonomousvision / transfuser

sensor fusion, [PAMI'23] TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving; [CVPR'21] Multi-Modal Fusion Transformer for End-to-End Autonomous Driving

From organization autonomousvision

bernwang / latte

sensor fusion, LATTE: Accelerating LiDAR Point Cloud Annotation via Sensor Fusion, One-Click Annotation, and Tracking

From user bernwang

changhao-chen / selective_sensor_fusion

sensor fusion, Webpage for Selective Sensor Fusion

From user changhao-chen

dk-sr / sfnd_lidar_obstacle_detection

sensor fusion, Sensor Fusion Nanodegree Project

From user dk-sr

huangcongqing / multi-sensor-fusion

sensor fusion, 多传感器融合（lidar radar camera）

From user huangcongqing

jackju-hit / sensorfusion-ukf

sensor fusion, 激光雷达和毫米波雷达数据融合基于无迹卡尔曼滤波算法c++工程项目

From user jackju-hit

jypjypjypjyp / lvio_fusion

sensor fusion, Lvio-Fusion: A Self-adaptive Multi-sensor Fusion SLAM Framework Using Actor-critic Method (IROS 2021)

From user jypjypjypjyp

kriswiner / mpu9150

sensor fusion, Arduino sketch for MPU9150 9DoF with AHRS sensor fusion

From user kriswiner

max-kazak / sensorfusion

sensor fusion, Combining sensor inputs from camera/lidar/radar to detect, track moving vehicles and estimate their speed and direction.

From user max-kazak

mithi / fusion-ekf

sensor fusion, An extended Kalman Filter implementation in C++ for fusing lidar and radar sensor measurements.

From user mithi

mithi / fusion-ekf-python

sensor fusion, An extended Kalman Filter implementation in Python for fusing lidar and radar sensor measurements

From user mithi

opendilab / interfuser

sensor fusion, [CoRL 2022] InterFuser: Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformer

From organization opendilab

palaghias / sensorfusion

sensor fusion, This project performs sensor fusion to track a mobile device's orientation. The data utilised are from three sensors: a) Accelerometer, b) Magnetic Field, d) Gyroscope. The sensor fusion is executed off-line. This project basically ports code developed by Paul Lawitzki from Android to Matlab/Octave. The Matlab/Octave code imports a CSV file with a given structure. Then, a strapdown integration system is developed by computing the orientation from two different components: a) Accelerometer - Magnetic Field and b) Gravity tracking through Gyroscope. Finally, the orientations from the two components are fused.

From user palaghias

Home Page: http://www.thousand-thoughts.com/2012/03/android-sensor-fusion-tutorial/

paulyehtw / lidar-and-radar-sensor-fusion-with-extended-kalman-filter

sensor fusion, Fusing Lidar and Radar data with Extended Kalman Filter (EKF)

From user paulyehtw

ptiwari0664 / sensorfusionnanodegree

sensor fusion, Learn to detect obstacles in lidar point clouds through clustering and segmentation, apply thresholds and filters to radar data in order to accurately track objects, and augment your perception by projecting camera images into three dimensions and fusing these projections with other sensor data. Combine this sensor data with Kalman filters to perceive the world around a vehicle and track objects over time.

From user ptiwari0664

rayryeng / udacity_sensor_fusion_nanodegree

sensor fusion, My work from the Udacity Sensor Fusion Nanodegree Program

From user rayryeng

sbussmann / sensor-fusion

sensor fusion, Use accelerometer and gyroscope data from smartphones to identify vehicle type (bus or car) and phone location (driver side or passenger side).

From user sbussmann

tuc-proaut / librsf

sensor fusion, A robust sensor fusion library for online localization.

From organization tuc-proaut

Home Page: https://mytuc.org/libRSF

tumftm / fusiontracking

sensor fusion, Multi-Modal Sensor Fusion and Object Tracking for Autonomous Racing

From user tumftm

turtlezhong / lvio-sam

sensor fusion, A Multi-sensor Fusion Odometry via Smoothing and Mapping.

From user turtlezhong

uditbhaskar19 / object_tracking_multi_sensor_fusion

sensor fusion, Sensor Fusion for Target Tracking

From user uditbhaskar19

uwembsys / sensorfusion

sensor fusion, Madgwick/Mayhony algorithm taken from http://www.x-io.co.uk/open-source-imu-and-ahrs-algorithms/

From organization uwembsys

yf291115925 / sfnd

sensor fusion, Udacity Sensor Fusion Code

From user yf291115925

yingtongwang / sensor-fusion-demo

sensor fusion, ＃Android的传感器融合演示[！[Build Status]（https://www.bitrise.io/app/46b5cf7adea1286f.svg?token=MZUhPFZvIBiaTSEinY9zUQ&branch=master）]（https://www.bitrise.io/app/46b5cf7adea1286f ）[！[Build Status]（https://travis-ci.org/apacha/sensor-fusion-demo.svg?branch=master）]（https://travis-ci.org/apacha/sensor-fusion-演示）[！[文档状态]（https://readthedocs.org/projects/sensor-fusion-demo/badge/?version=latest）]（http://sensor-fusion-demo.readthedocs.io/en/最新/？徽章=最新）本应用程序演示了各种传感器和传感器融合的功能。陀螺仪，加速度计和罗盘的数据以不同的方式组合，结果显示为可以通过旋转设备旋转的立方体。阅读完整的文档[这里]（http://sensor-fusion-demo.readthedocs.io）。该应用中的主要新颖之处在于虚拟传感器的融合：**改进的方位传感器1 **和**改进的方位传感器2 **将Android旋转矢量与虚拟陀螺仪传感器融合，以获得以前未知的稳定性的姿态估计和精度。除了这两个传感器，以下传感器可用于比较： - 改进的方向传感器1（Android旋转矢量和校准陀螺仪的传感器融合 - 不太稳定但更准确） - 改进的方向传感器2（Android旋转矢量的传感器融合和校准陀螺仪 - 更稳定但不太准确） - Android旋转矢量（加速度计+陀螺仪+罗盘）的卡尔曼滤波器融合 - 校准陀螺仪（加速度计+陀螺仪+指南针卡尔曼滤波器的独立结果） - 重力+指南针 - 加速度计+指南针本应用被开发用于展示为[我的论文“传感器融合为移动设备上强大的户外增强现实跟踪”开发的传感器融合方法]（http://my-it.at/media/MasterThesis-Pacha.pdf）在[人类接口技术实验室新西兰]（http://www.hitlabnz.org）。##构建和安装此项目是基于Gradle的Android Studio项目。如果您只想尝试一下，它也会在[Google Play商店]（https://play.google.com/store/apps/details?id=org.hitlabnz.sensor_fusion_demo）中发布。##贡献1.分叉2.创建您的功能分支（`git checkout -b my-new-feature`）3.提交你的更改（`git commit -am'添加一些功能'）4.推到分支（`git push origin my-new-feature`）5.根据MIT许可证创建新的Pull Request ##许可证。版权所有，2017年由[亚历山大·帕查]（http://alexanderpacha.com）和[人力资源技术实验室新西兰]（http://www.hitlabnz.org）。特此授权任何获得本软件和相关文档文件（“软件”）副本的人免费处理本软件，包括但不限于使用，复制，修改，合并的权利，发布，分发，再许可和/或出售本软件的副本，并允许提供本软件的人员遵守以下条件：上述版权声明和本许可声明应包含在所有副本中或软件的主要部分。该软件“按原样”提供，不附带任何明示或暗示的保证，包括但不限于适销性，适用于特定用途和不侵权的保证。在任何情况下，作者或版权所有者均不对任何索赔，损害或其他责任负责，无论是否因与本软件或本软件的使用或其他交易相关的任何合同，侵权行为或其他方面的行为软件。此应用程序还使用Android开放源代码项目的部分，它们是根据[Apache许可证版本2.0]（http://www.apache.org/licenses/LICENSE-2.0）许可的。##数据隐私声明本应用程序不存储或传输任何数据。

From user yingtongwang

youngger / udacity-sensorfusion-nanodegree

sensor fusion, This is my Sensor Fusion projects with Udacity ND.

From user youngger

yyccr / location

sensor fusion, Smartphone navigation positionning, fusion GPS and IMU sensors.

From user yyccr