Swarm Exploration with Pocketdrones

The aim of this project is to investigate and design an autonomous swarm of Micro Air Vehicles (MAVs)to do multi-robot exploration of an unstructured indoor environment. These so called pocket drones are small quadroters with a mass in the order of 20 grams and a diameter of 10 cm. It can maneuve ritself through small corridors, windows and can reach different levels of a building. A swarm of these pocket drones is ideal for the fast exploration of a building during a search and rescue mission for instance.

However, these pocket drones have strict limitations on their on-board energy, sensing and processing capabilities. The challenge is to combine the needed functionalities, in terms of obstacle avoidance, exploration and coordination with the other drones. Inspiration can be drawn from honeybees, since an individual bee does not have many capabilities just by itself, but a swarm of them is able explore an entire field of flowers. This inspiration will help to develop efficient algorithms for multi-robot exploration with the pocket drones.
There are aspects and challenges to be considered for the design of a swarm of pocket drones. Low level navigation, which stand for simple behaviors as drift stabilization and obstacle avoidance, is essential to make the MAV fly. This will be executed with an on-board stereo vision system. The emphasis here is on efficiency, as the pocket drone need to do so much more than only these rudimentary tasks. The pocket drone also needs to know its environment and should decide where to explore next, which are more high level navigations tasks. Here the challenge is to design efficient localization and mapping algorithms for limited on-board processing of the pocket drone based on its vision system.
The last challenge is the multi-robot coordination, which enhances the pocket drones performance by enhancing their individual abilities as a swarm. The challenge is to enable the drones to share the generated map and locations and decision making in task coordination with limited communication and sensing capabilities. Since no central computer is used, the focus is on decentralized optimal control as the drones must make decisions themselves to benefit the overall search mission.


  • [PDF] [DOI] K. McGuire, G. de Croon, C. de Wagter, B. Remes, K. Tuyls, and H. Kappen, “Local histogram matching for efficient optical flow computation applied to velocity estimation on pocket drones,” in 2016 ieee international conference on robotics and automation (icra), 2016, pp. 3255-3260.
    author = {K. McGuire and G. de Croon and C. de Wagter and B. Remes and K. Tuyls and H. Kappen},
    title = {Local histogram matching for efficient optical flow computation applied to velocity estimation on pocket drones},
    booktitle = {2016 IEEE International Conference on Robotics and Automation (ICRA)},
    year = {2016},
    pages = {3255-3260},
    month = {May},
    pdf = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7487496},
    doi = {10.1109/ICRA.2016.7487496},
    keywords = {image sequences;mobile robots;robot vision;velocity measurement;STM32F4 microprocessor;autonomous flight;edge histograms;local histogram matching;local optical flow;optical flow computation efficiency;pocket drones;stereo-camera;subpixel flow determination;time horizon adaptation;velocity control-loop;velocity estimation;velocity measurements;Cameras;Drones;Estimation;Histograms;Image edge detection;Optical imaging;Optical sensors}


  • [DOI] K. McGuire, G. de Croon, K. Tuyls, and B. Kappen, “Efficient optical flow and stereo vision for velocity estimation and obstacle avoidance on an autonomous pocket drone,” Ieee robotics and automation letters, vol. 2, iss. 2, pp. 1070-1076, 2017.
    title = {Efficient Optical Flow and Stereo Vision for Velocity Estimation and Obstacle Avoidance on an Autonomous Pocket Drone},
    journal = {IEEE Robotics and Automation Letters},
    year = {2017},
    volume = {2},
    issue = {2},
    number = {2},
    pages = {1070-1076},
    note = {},
    issn = {2377-3766},
    doi = {10.1109/LRA.2017.2658940},
    author = {McGuire, Kimberly and de Croon, Guido and Tuyls, Karl and Kappen, Bert},
  • K. McGuire, M. Coppola, C. De~Wagter, and G. de~Croon, “Towards autonomous navigation of multiple pocket-drones in real-world environments,” in Ieee/rsj international conference on intelligent robots and systems (iros), 2017.
    title={Towards Autonomous Navigation of Multiple Pocket-Drones in Real-World Environments},
    author={McGuire, Kimberly and Coppola, Mario and De~Wagter, Christophe and de~Croon, Guido},
    booktitle={IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},


  • [PDF] [DOI] M. Coppola, K. N. McGuire, K. Y. W. Scheper, and G. C. H. E. de Croon, “On-board communication-based relative localization for collision avoidance in micro air vehicle teams,” Autonomous robots, vol. 42, iss. 8, p. 1787–1805, 2018.
    author="Coppola, Mario
    and McGuire, Kimberly N.
    and Scheper, Kirk Y. W.
    and de Croon, Guido C. H. E.",
    title="On-board communication-based relative localization for collision avoidance in Micro Air Vehicle teams",
    journal="Autonomous Robots",
  • [DOI] G. J. J. Van Dalen, K. N. McGuire, and G. C. H. E. De Croon, “Visual homing for micro aerial vehicles using scene familiarity,” Unmanned systems, vol. 6, iss. 2, pp. 119-130, 2018.
    author={Van Dalen, Gerald J. J. and McGuire, Kimberly. N. and De Croon, Guido C. H. E.},
    title={Visual Homing for Micro Aerial Vehicles Using Scene Familiarity},
    journal={Unmanned Systems},
    doi = {10.1142/S230138501850005X},
    month = {jun}


  • [PDF] [DOI] S. van der Helm, M. Coppola, K. N. McGuire, and G. C. H. E. de Croon, “On-board range-based relative localization for micro air vehicles in indoor leader–follower flight,” Autonomous robots, 2019.
    author="van der Helm, Steven
    and Coppola, Mario
    and McGuire, Kimberly N.
    and de Croon, Guido C. H. E.",
    title="On-board range-based relative localization for micro air vehicles in indoor leader--follower flight",
    journal="Autonomous Robots",
    pdf = "https://bit.ly/2HYDkgO"
  • [DOI] K. N. McGuire, C. De Wagter, K. Tuyls, H. J. Kappen, and G. C. H. E. de Croon, “Minimal navigation solution for a swarm of tiny flying robots to explore an unknown environment,” Science robotics, vol. 4, iss. 35, 2019.
    author = {McGuire, K. N. and De Wagter, C. and Tuyls, K. and Kappen, H. J. and de Croon, G. C. H. E.},
    title = {Minimal navigation solution for a swarm of tiny flying robots to explore an unknown environment},
    volume = {4},
    number = {35},
    elocation-id = {eaaw9710},
    year = {2019},
    doi = {https://doi.org/10.1126/scirobotics.aaw9710},
    publisher = {Science Robotics},
    URL = {https://robotics.sciencemag.org/content/4/35/eaaw9710},
    journal = {Science Robotics}
  • [DOI] K. N. McGuire, G. C. H. E. de Croon, and K. Tuyls, “A comparative study of bug algorithms for robot navigation,” Robotics and autonomous systems, vol. 121, p. 103261, 2019.
    title = "A comparative study of bug algorithms for robot navigation",
    journal = "Robotics and Autonomous Systems",
    volume = "121",
    pages = "103261",
    year = "2019",
    issn = "0921-8890",
    doi = "https://doi.org/10.1016/j.robot.2019.103261",
    url = "http://www.sciencedirect.com/science/article/pii/S0921889018306687",
    author = "K.N. McGuire and G.C.H.E. de Croon and K. Tuyls",
    keywords = "Bug algorithms, Robotic navigation, Comparative study, Limited sensing, Indoor navigation",
    abstract = "This paper presents a literature survey and a comparative study of Bug Algorithms, with the goal of investigating their potential for robotic navigation. At first sight, these methods seem to provide an efficient navigation paradigm, ideal for implementations on tiny robots with limited resources. Closer inspection, however, shows that many of these Bug Algorithms assume perfect global position estimate of the robot which in GPS-denied environments implies considerable expenses of computation and memory — relying on accurate Simultaneous Localization And Mapping (SLAM) or Visual Odometry (VO) methods. We compare a selection of Bug Algorithms in a simulated robot and environment where they endure different types noise and failure-cases of their on-board sensors. From the simulation results, we conclude that the implemented Bug Algorithms’ performances are sensitive to many types of sensor-noise, which was most noticeable for odometry-drift. This raises the question if Bug Algorithms are suitable for real-world, on-board, robotic navigation as is. Variations that use multiple sensors to keep track of their progress towards the goal, were more adept in completing their task in the presence of sensor-failures. This shows that Bug Algorithms must spread their risk, by relying on the readings of multiple sensors, to be suitable for real-world deployment."

2 thoughts on “Swarm Exploration with Pocketdrones

Comments are closed.