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https://github.com/MapIV/eagleye

Precise localization based on GNSS and IMU.
https://github.com/MapIV/eagleye

gnss imu localization ros ros2

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Precise localization based on GNSS and IMU.

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README 

        





![example workflow](https://github.com/MapIV/eagleye/actions/workflows/build.yml/badge.svg)



[Demo Video](https://youtu.be/u8Nan38BkDw)



[![](http://img.youtube.com/vi/u8Nan38BkDw/0.jpg)](http://www.youtube.com/watch?v=u8Nan38BkDw "Eagleye")



## What is Eagleye



Eagleye is an open-source software for vehicle localization utilizing GNSS and IMU[[1]](https://www.researchgate.net/publication/329619280_Low-cost_Lane-level_Positioning_in_Urban_Area_Using_Optimized_Long_Time_Series_GNSS_and_IMU_Data). Eagleye provides highly accurate and stable vehicle position and orientation by using GNSS Doppler[[2]](https://www.jstage.jst.go.jp/article/jsaeronbun/44/1/44_20134048/_article/-char/en)[[3]](https://www.jstage.jst.go.jp/article/jsaeijae/3/2/3_20124032/_article/-char/ja)[[4]](https://ieeexplore.ieee.org/document/6236946)[[5]](https://www.researchgate.net/publication/290751834_Automotive_positioning_based_on_bundle_adjustment_of_GPS_raw_data_and_vehicle_trajectory)[[6]](https://ci.nii.ac.jp/naid/10029931657/). The flowchart of the algorithm is shown in the figure below. The algorithms in this software are based on the outcome of the research undertaken by [Machinery Information Systems Lab (Meguro Lab)](https://www2.meijo-u.ac.jp/~meguro/index.html) in Meijo University.



![Flowchart of Eagleye](docs/flowchart.png)



## Architecture



![Architecture of Eagleye](docs/eagleye_architecture.drawio.svg)



## Recommended Sensors

**GNSS receiver**



* [Ublox ZED-F9P](https://www.u-blox.com/en/product/zed-f9p-module) / [C099-F9P](https://www.u-blox.com/en/product/c099-f9p-application-board)

* [Septentrio Mosaic development kit with GNSS antenna](https://shop.septentrio.com/en/shop/mosaic-x5-devkit)



**GNSS Antenna**



* [Ublox ANN-MB Series](https://www.u-blox.com/en/product/ann-mb-series)

* [Tallysman TW2710](http://www.tallysman.com/index.php/gnss/products/antennas-gpsbeidougalileoglonass/tw2710/)



**IMU**

* [Tamagawa Seiki TAG300 Series](http://mems.tamagawa-seiki.com/en/product/)

* [ANALOG DEVICES ADIS16475](https://www.analog.com/products/adis16475.html#product-overview)



**Wheel speed sensor**



* Eagleye uses vehicle speed acquired from CAN bus.



## How to install



### RTKLIB



Clone and Build MapIV's fork of [RTKLIB](https://github.com/MapIV/RTKLIB/tree/rtklib_ros_bridge). You can find more details about RTKLIB [here](http://www.rtklib.com/).



	sudo apt-get install gfortran

	cd $HOME

	git clone -b rtklib_ros_bridge_b34 https://github.com/MapIV/RTKLIB.git

	cd $HOME/RTKLIB/lib/iers/gcc/

	make

	cd $HOME/RTKLIB/app/consapp

	make



### ROS Packages



Clone and build the necessary packages for Eagleye.



	pip install vcstool

	cd $HOME/catkin_ws/src

	git clone https://github.com/MapIV/eagleye.git -b main-ros1

	vcs import . < eagleye/eagleye.repos

	sudo apt-get install -y libgeographic-dev geographiclib-tools geographiclib-doc

	sudo geographiclib-get-geoids best

	sudo mkdir /usr/share/GSIGEO

	sudo cp llh_converter/data/gsigeo2011_ver2_1.asc /usr/share/GSIGEO/

	cd ..

	rosdep install --from-paths src --ignore-src -r -y

	catkin_make -DCMAKE_BUILD_TYPE=Release



## Configuration



### GNSS



[ublox f9p settings](docs/gnss/f9p.md)



[septentrio mosaic settings](docs/gnss/mosaic.md)



### IMU



1. IMU settings.



* Output rate 50Hz



2. Check the rotation direction of z axis of IMU being used. If you look from the top of the vehicle, if the left turn is positive, set `pitch` to `3.14159` in `eagleye/eagleye_util/tf/config/sensors_tf.yaml`.



		 pitch: 3.14159



## Start each sensor driver



1. Check if wheel speed (vehicle speed) is published in `/can_twist` topic.



* Topic name: /can_twist

* Message type: geometry_msgs/TwistStamped twist.liner.x



2. Check if the IMU data is published in `/imu/data_raw` topic.



3. Start RTKLIB.



	ex. single point positioning



		cd $HOME/RTKLIB

		bash rtklib_ros_bridge_single.sh



	ex. Real Time Kinematic



 		cd $HOME/RTKLIB

		bash rtklib_ros_bridge_meijo_rtk.sh



4. Check if RTKLIB is working by execute the following command in the terminal. If the RTKLIB is working correctly, positioning information is appeared continuously in the terminal.



		status 0.1



5. Start rtklib_ros_bridge.



		roslaunch rtklib_bridge rtklib_bridge.launch



6. Start nmea_comms in f9p or nmea_ros_bridge in mosaic.



		roslaunch nmea_comms f9p_nmea_sentence.launch



   or



		roslaunch nmea_ros_bridge nmea_udp.launch



## eagleye_rt



- [eagleye_rt](eagleye_rt) : real-time version



## Optional Features



### can_less mode



While normal eagleye requires CAN (wheel speed) information, this option allows localization estimation with GNSS/IMU alone, without vehicle speed.



However, in this mode, note the following

- Accuracy degrades in non-open sky environments.

- RTK positioning is required.

- Localization estimating is not possible when driving backward.



To use this mode

- Use launch/eagleye_rt_can_less.launch for eagleye_rt instead of launch/eagleye_rt.launch.



### dual antenna mode



This option allows for more immediate heading estimatiion, and allows GNSS to estimate heading even at low speeds.



To use this mode

- Use launch/eagleye_rt_dualantenna.launch for eagleye_rt instead of launch/eagleye_rt.launch.



## Sample data

### ROSBAG



| No. | Date | Place | Sensors | Link |

|-----|------|-------|---------| ---- |

|1|2020/01/27|Moriyama, Nagoya
[route](https://www.google.com/maps/d/edit?mid=1pK4BgrGtoo14nguArDf-rZDqIL5Cg-v5&usp=sharing)|GNSS: Ublox F9P
IMU: Tamagawa AU7684
LiDAR: Velodyne HDL-32E|[Download](https://www.dropbox.com/s/pfs307qn7gfeou5/eagleye_sample_20200127.bag?dl=0)|

|2|2020/07/15|Moriyama, Nagoya
[route](https://www.google.com/maps/d/edit?mid=1DnXfZBTSsHpWlzTAcENmFxo17r3PxGxM&usp=sharing)|GNSS: Ublox F9P with RTK
IMU: Tamagawa AU7684
LiDAR: Velodyne VLP-32C|[Download](https://www.dropbox.com/s/w9ag6gs17bi80st/eagleye_sample_20200715.bag?dl=0)



### Maps

The 3D maps (point cloud and vector data) of the route is also available from [Autoware sample data](https://drive.google.com/file/d/1Uwp9vwvcZwaoZi4kdjJaY55-LEXIzSxf/view).



## Research Papers for Citation



1. A. Takanose, et., al., "Eagleye: A Lane-Level Localization Using Low-Cost GNSS/IMU", Intelligent Vehicles (IV) workshop, 2021 [Link](https://ieeexplore.ieee.org/document/9669209)



1. J Meguro, T Arakawa, S Mizutani, A Takanose, "Low-cost Lane-level Positioning in Urban Area Using Optimized Long Time Series GNSS and IMU Data", International Conference on Intelligent Transportation Systems(ITSC), 2018 [Link](https://www.researchgate.net/publication/329619280_Low-cost_Lane-level_Positioning_in_Urban_Area_Using_Optimized_Long_Time_Series_GNSS_and_IMU_Data)



1. Takeyama Kojiro, Kojima Yoshiko, Meguro Jun-ichi, Iwase Tatsuya, Teramoto Eiji, "Trajectory Estimation Based on Tightly Coupled Integration of GPS Doppler and INS" -Improvement of Trajectory Estimation in Urban Area-, Transactions of Society of Automotive Engineers of Japan   44(1) 199-204, 2013 [Link](https://www.jstage.jst.go.jp/article/jsaeronbun/44/1/44_20134048/_article/-char/en)



1. Junichi Meguro, Yoshiko Kojima, Noriyoshi Suzuki, Teramoto Eiji, "Positioning Technique Based on Vehicle Trajectory Using GPS Raw Data and Low-cost IMU", International Journal of Automotive Engineering 3(2) 75-80,  2012 [Link](https://www.jstage.jst.go.jp/article/jsaeijae/3/2/3_20124032/_article/-char/ja)



1. K Takeyama, Y Kojima, E Teramoto, "Trajectory estimation improvement based on time-series constraint of GPS Doppler and INS in urban areas", IEEE/ION Position, Location and Navigation Symposium(PLANS), 2012 [Link](https://ieeexplore.ieee.org/document/6236946)



1. Junichi Meguro, Yoshiko Kojima, Noriyoshi Suzuki, Eiji Teramoto, "Automotive Positioning Based on Bundle Adjustment of GPS Raw Data and Vehicle Trajectory", International Technical Meeting of the Satellite Division of the Institute of Navigation (ION), 2011 [Link](https://www.researchgate.net/publication/290751834_Automotive_positioning_based_on_bundle_adjustment_of_GPS_raw_data_and_vehicle_trajectory)



1. Yoshiko Kojima, et., al., "Precise Localization using Tightly Coupled Integration based on Trajectory estimated from GPS Doppler", International Symposium on Advanced Vehicle Control(AVEC), 2010 [Link](https://ci.nii.ac.jp/naid/10029931657/)



## License

Eagleye is provided under the [BSD 3-Clause](https://github.com/MapIV/eagleye/blob/master/LICENSE) License.



## Contacts



If you have further question, email to [email protected].