- 1 Overview
- 2 Project Summary
- 3 Applications Demonstrations
- 4 Demonstrations
- 4.1 Demo1: Arming a drone through Dronemap Planner Cloud
- 4.2 Demo2: Drones' auto-detection in Dronemap Planner
- 4.3 Demo3: Dronemap Planner Mission Control of MAVLink Drone Through the Internet
- 4.4 Demo4: Monitoring and mission control of multiple simulated drones
- 4.5 Demo5: Autonomous Mission with GoPro Camera View on Drone using Dronemap Planner
- 5 Publications
- Principal Investigator: Anis Koubaa
- Duration: 1 year (October 2015 - September 2016)
- Funding Agency: King Abdul-Aziz City for Science and Technology
- WP 1. Software Engineering of the Cloud System
- WP 2. Configuration of Micro UAVs and its Interfaces
- WP 3. Implementation and Development
- WP 4. Experimentation, testing and validation
The following video provides a comprehensive yet concise summary about the contributions of the Dronemap Project (20 minutes)
Demo: Follower Application: Real-Time Person Tracking with a Drone using Dronemap Planner Cloud (Feb 2017)
In this demo, I show an ardupilot simulated drone that tracks the location of a moving person. The moving person control the following mission through an Android device connect to Internet through 3G connection, and sends command to the Dronemap Planner cloud to allocate a drone, and start/stop a mission. The cloud will forward messages to the drone to execute them.
After the mission has started, the drone will takeoff and head towards the walking person and keep following him as he moves. The Android application keeps sending new locations of the moving person to the cloud, which forward them to the drone to move toward that new location.
In this experiment, the average distance between the drone and the walking person was about 4 meters.
For more information about Dronemap Planner, refer to the project web page http://wiki.coins-lab.org/index.php?title=Dronemap
Demo1: Arming a drone through Dronemap Planner Cloud
In this demo, I show a small test on how to arm a drone connected to Dronemap Planner.
Demo2: Drones' auto-detection in Dronemap Planner
In this video, I illustrate how Dronemap Planner is able to auto-detect drones connected to the the cloud automatically. I used Simulated drones with SITL. Real drones will also operate exactly in the same way provided that they do stream MAVLink messages.
Demo3: Dronemap Planner Mission Control of MAVLink Drone Through the Internet
This demonstration shows the mission control of MAVLink drones using the dronemap planner cloud through Internet.
Dronemap Planner is a service-oriented cloud based drone management system that provides access to drones through web services (SOAP and REST), schedule missions and promote collaboration between drones. A modular cloud proxy server was developed; it acts as a mediator between drones and users. Communication between drones, users and the Dronemap Planner cloud is provided by the MAVLink protocol, which is supported by commodity drones.
Demo4: Monitoring and mission control of multiple simulated drones
In this demo, I show how dronemap planner can be used to monitor and control the mission of multiple drones simultaneously in real-time
Demo5: Autonomous Mission with GoPro Camera View on Drone using Dronemap Planner
In this video, I show an autonomous mission for a drone with Dronemap Planner and a view from GoPro camera while executing the mission
Anis Koubâa (Editor), Robot Operating System – The Complete Reference (Edition 2), in the series Studies in Systems, Decision and Control, Springer International Publishing, to appear on Feb 2017 (under press – contains 15 chapters, second edition Springer book on ROS).
Rihab Chaâri, Fatma Ellouze, Anis Koubâa, Basit Qureshi, Nuno Pereira, Habib Youssef, Eduardo Tovar, Cyber-physical systems clouds: A survey, Computer Networks, Volume 108, 24 October 2016, Pages 260-278, ISSN 1389-1286, http://dx.doi.org/10.1016/j.comnet.2016.08.017. (http://www.sciencedirect.com/science/article/pii/S1389128616302699)
Basit Qureshi, Anis Koubaa,, Yasir Javed, Geyong Min, Performance of Low-Cost Low-Energy ARM based Cloud Environments: A Hadoop Case Study. submitted to IEEE Transactions on Cloud Computing.
Anis Koubaa, Basit Qureshi, Mohamed-Foued Sriti, Yasir Javed, and Eduardo Tovar, Dronemap Planner: A Cloud-Based Mission Control System for the Internet-of-Drones, to be submitted to the IEEE Journal of Internet-of-Things.
Anis Koubaa, Service-Oriented Robotic Computing, invited chapter in Springer on an Encyclopedia of Robotics, Section: “Task and Robot Programming", M.H. Ang, O. Khatib, and B. Siciliano, Mid 2017 (In progress).
Basit Qureshi, Yasir Javed, Anis Koubâa, Mohamed-Foued Sriti, Maram Alajlan, Performance of a Low Cost Hadoop Cluster for Image Analysis in Cloud Robotics Environment, Procedia Computer Science, Volume 82, 2016, Pages 90-98, ISSN 1877-0509, http://dx.doi.org/10.1016/j.procs.2016.04.013. (http://www.sciencedirect.com/science/article/pii/S1877050916300278)
Basit Qureshi, Anis Koubaa, Mohamed-Foued Sriti, Yasir Javed, and Maram Alajlan. 2016. Poster: Dronemap - A Cloud-based Architecture for the Internet-of-Drones. In Proceedings of the 2016 International Conference on Embedded Wireless Systems and Networks (EWSN '16). Junction Publishing, USA, 255-256. (Class A conference)
Sahar Trigui, Anis Koubaa, Omar Cheikhrouhou, Basit Qureshi, Habib Youssef A clustering market-based approach for multi-robot emergency response applications, The IEEE International Conference on Autonomous Robot Systems and Competitions, Bragança, Portugal, on May 4-6, 2016.
Anis Koubaa, Basit Qureshi, Mohamed-Foued Sriti, Yasir Javed, and Eduardo Tovar, Dronemap Planner: A Service-Oriented Cloud-Based Management System for the Internet-of-Drones, submitted to The 32nd ACM Symposium on Applied Computing, Internet-of-Things Track, April 3-7, 2017, Marrakesh, Morocco (Class B conference)
Maram Alajlan, Anis Koubaa, Basit Qureshi, ROSLink: Bridging ROS with the Internet-of-Things for Cloud Robotics , submitted.