Update README.md

README.md

@@ -38,7 +38,7 @@ For a closed-source version of ORB-SLAM3 for commercial purposes, please contact
 
 If you use ORB-SLAM3 in an academic work, please cite:
 
-    @article{ORBSLAM3_2020,
+    @article{ORBSLAM3_TRO,
       title={{ORB-SLAM3}: An Accurate Open-Source Library for Visual, Visual-Inertial 
                and Multi-Map {SLAM}},
       author={Campos, Carlos AND Elvira, Richard AND G\´omez, Juan J. AND Montiel, 
@@ -95,7 +95,23 @@ chmod +x build.sh
 
 This will create **libORB_SLAM3.so**  at *lib* folder and the executables in *Examples* folder.
 
-# 4. EuRoC Examples
+# 4. Running ORB-SLAM3 with your camera
+
+Directory `Examples` contains several demo programs and calibration files to run ORB-SLAM3 in all sensor configurations with Intel Realsense cameras T265 and D435i. The steps needed to use your own camera are: 
+
+1. Calibrate your camera following `Calibration_Tutorial.pdf` and write your calibration file `your_camera.yaml`
+
+2. Modify one of the provided demos to suit your specific camera model, and build it
+
+3. Connect the camera to your computer using USB3 or the appropriate interface
+
+4. Run ORB-SLAM3. For example, for our D435i camera, we would execute:
+
+```
+./Examples/Stereo-Inertial/stereo_inertial_realsense_D435i Vocabulary/ORBvoc.txt ./Examples/Stereo-Inertial/RealSense_D435i.yaml
+```
+
+# 5. EuRoC Examples
 [EuRoC dataset](http://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets) was recorded with two pinhole cameras and an inertial sensor. We provide an example script to launch EuRoC sequences in all the sensor configurations.
 
 1. Download a sequence (ASL format) from http://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets
@@ -115,7 +131,7 @@ Execute the following script to process sequences and compute the RMS ATE:
 ./euroc_eval_examples
 ```
 
-# 5. TUM-VI Examples
+# 6. TUM-VI Examples
 [TUM-VI dataset](https://vision.in.tum.de/data/datasets/visual-inertial-dataset) was recorded with two fisheye cameras and an inertial sensor.
 
 1. Download a sequence from https://vision.in.tum.de/data/datasets/visual-inertial-dataset and uncompress it.
@@ -135,7 +151,7 @@ Execute the following script to process sequences and compute the RMS ATE:
 ./tum_vi_eval_examples
 ```
 
-# 6. ROS Examples
+# 7. ROS Examples
 
 ### Building the nodes for mono, mono-inertial, stereo, stereo-inertial and RGB-D
 Tested with ROS Melodic and ubuntu 18.04.
@@ -212,8 +228,8 @@ Once ORB-SLAM3 has loaded the vocabulary, press space in the rosbag tab.
   rosrun rosbag fastrebag.py dataset-room1_512_16.bag dataset-room1_512_16_small_chunks.bag
   ```
 
-# 7. Running time analysis
+# 8. Running time analysis
 A flag in `include\Config.h` activates time measurements. It is necessary to uncomment the line `#define REGISTER_TIMES` to obtain the time stats of one execution which is shown at the terminal and stored in a text file(`ExecTimeMean.txt`).
 
-# 8. Calibration
+# 9. Calibration
 You can find a tutorial for visual-inertial calibration and a detailed description of the contents of valid configuration files at  `Calibration_Tutorial.pdf`