VIssvo

Base:https://github.com/kokerf/ssvo

Visual–Inertial Semi-direct sparse odometry

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ssvo

video of running in rpg_urban dataset, and live video.

1. Prerequisites

1.1 OpenCV

OpenCV 3.1.0 is used in this code.

1.2 Eigen3

sudo apt-get install libeigen3-dev

1.3 Sophus

This code use the template implement of Sophus. Recommend the latest released version v1.0.0

1.4 glog

This code use glog for logging.

sudo apt-get install libgoogle-glog-dev

1.5 Ceres

Use Ceres-Slover to slove bundle adjustment. Please follow the installation page to install.

1.6 Pangolin

This code use Pangolin to display the map reconstructed. When install, just follow the README.md file.

1.7 DBow3

After build and install, copy the file FindDBoW3.cmake to the directory cmake_modules

2. Usages & Evalution

the Euroc Dataset is used for evalution. In the project directory, run the demo by the following commond

./bin/monoVO ./config/euroc.yaml dataset_image_path dataset_csv_file

for example, the dataset MH_01_easy's directory is in /home, just run

./bin/monoVO ./config/euroc.yaml ~/MH_01_easy/cam0/data ~/MH_01_easy/cam0/data.csv

finally, there will be a trajectory.txt saved, and you can use the evo to evaluate.