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3dv_tutorial

An Invitation to 3D Vision: A Tutorial for Everyone

a-loam

Advanced implementation of LOAM

allan_variance_ros

ROS compatible tool to generate Allan Deviation plots

autoware_ai

autoware_ai_utilities

azure-kinect-sensor-sdk

A cross platform (Linux and Windows) user mode SDK to read data from your Azure Kinect device.

blackfly_nodelet

ROS driver for the Flir Blackfly cameras using the Spinnaker SDK

canny-evt

cerberus

Visual-Inertial-Leg Odometry For Legged Robots

cheetah_inekf_realtime

code_utils

my code utils

ct_icp

CT-ICP: Continuous-Time LiDAR Odometry

deep-learning-with-python

Example projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.

depthimage_to_laserscan

Converts a depth image to a laser scan for use with navigation and localization.

dm-vio

Coming soon: Source code forthe paper DM-VIO: Delayed Marginalization Visual-Inertial Odometry

dotfiles

Personal dotfiles for *NIX systems

dso

dso个人注释版

dso-1

Direct Sparse Odometry

dso_ros

ROS wrapper for dso

esvo

This repository maintains the implementation of "Event-based Stereo Visual Odometry".

ev-flownet

Code for the paper "EV-FlowNet: Self-Supervised Optical Flow for Event-based Cameras"

evdodgenet

EVDodgeNet: Deep Dynamic Obstacle Dodging with event cameras

event-based_object_catching_anymal

Code for "Event-based Agile Object Catching with a Quadrupedal Robot", Forrai et al. ICRA'23

event_based_vo-vio-slam

Our Works in Event-based VO/VIO/SLAM

event_representation

Event-based camera data representation and processing. Some common representations and reference codes.

events_contrast_maximization

A python library for contrast maximization and voxel creation using events

evo

Python package for the evaluation of odometry and SLAM

fast-dynamic-vision

Detecting and Tracking Dynamic Objects with Event and Depth Sensing

fast_lio

A computationally efficient and robust LiDAR-inertial odometry (LIO) package

faster-lio

Faster-LIO: Lightweight Tightly Coupled Lidar-inertial Odometry using Parallel Sparse Incremental Voxels