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Zhang Liqiang's Projects

advio icon advio

An Authentic Dataset for Visual-Inertial Odometry

ailearning icon ailearning

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

cerebro icon cerebro

Intelligent place recognition module for vins-fusion

cheatsheets-ai icon cheatsheets-ai

Essential Cheat Sheets for deep learning and machine learning researchers

citylearn icon citylearn

Official implementation of paper "CityLearn: Diverse Real-World Environments for Sample-Efficient Navigation Policy Learning" by M. Chancán (ICRA 2020) https://doi.org/10.1109/ICRA40945.2020.9197336

crisp icon crisp

Camera-to-IMU calibration and synchronization toolbox

deepconvlstm icon deepconvlstm

Deep learning framework for wearable activity recognition based on convolutional and LSTM recurretn layers

deepibl icon deepibl

Stochastic Attraction-Repulsion Embedding for Large Scale Localization

deepseqslam icon deepseqslam

The Official Deep Learning Framework for Route-based Place Recognition

demon icon demon

DeMoN: Depth and Motion Network

denoise-imu-gyro icon denoise-imu-gyro

Convolutional Neural Networks for Denoising Gyroscopes of Low-Cost IMUs

dpc-net icon dpc-net

Deep Pose Correction for Visual Localization

estimation-algorithms icon estimation-algorithms

Estimation-algorithms includes MATLAB functions for the EKF, UKF, Particle Filter, and their computationally efficient variants.

flynet icon flynet

Official PyTorch implementation of paper "A Hybrid Compact Neural Architecture for Visual Place Recognition" by M. Chancán (RA-L & ICRA 2020) https://doi.org/10.1109/LRA.2020.2967324

glmocap icon glmocap

运动捕捉系统GLMocap包括多相机硬件开源方案和上位机软件算法方案的低成本运动捕捉系统。目前设计指标为低成本实现毫米级空间定位,辅助无人机等有室内定位需求的装置和设备。

gnss-ins-sim icon gnss-ins-sim

Open-source GNSS + inertial navigation, sensor fusion simulator. Motion trajectory generator, sensor models, and navigation

hfnet icon hfnet

From Coarse to Fine: Robust Hierarchical Localization at Large Scale with HF-Net (https://arxiv.org/abs/1812.03506)

hugadb icon hugadb

Database for human gait analysis consisting of continues recordings of combined activities, such as walking, running, taking stairs up and down, sitting down, and so on; and the data recorded are segmented and annotated. Data were collected from a body sensor network consisting of six wearable inertial sensors (accelerometer and gyroscope) located on the right and left thighs, shins, and feet. Additionally, two EMG sensors were used on the quadriceps (front thigh) to measure muscle activity.

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