Behavior-Based Control for an Aerial Robotic Swarm in Surveillance Missions

Aerial robotic swarms have shown benefits for performing search and surveillance missions in open spaces in the past. Among other properties, these systems are robust, scalable and adaptable to different scenarios. In this work, we propose a behavior-based algorithm to carry out a surveillance task in a rectangular area with a flexible number of quadcopters, flying at different speeds. Once the efficiency of the algorithm is quantitatively analyzed, the robustness of the system is demonstrated with 3 different tests: loss of broadcast messages, positioning errors, and failure of half of the agents during the mission. Experiments are carried out in an indoor arena with micro quadcopters to support simulation results. Finally, a case study is proposed to show a realistic implementation in the test bed.

[1]  Vijay Kumar,et al.  A Survey on Aerial Swarm Robotics , 2018, IEEE Transactions on Robotics.

[2]  Antonio Barrientos Cruz,et al.  Control optimization of an aerial robotic swarm in a search task and its adaptation to different scenarios , 2018, J. Comput. Sci..

[3]  Richard J. Duro,et al.  Swarm intelligence based approach for real time UAV team coordination in search operations , 2011, 2011 Third World Congress on Nature and Biologically Inspired Computing.

[4]  Antonio Barrientos,et al.  Monitoring traffic in future cities with aerial swarms: Developing and optimizing a behavior-based surveillance algorithm , 2019, Cognitive Systems Research.

[5]  Nikhil Nigam,et al.  Control of Multiple UAVs for Persistent Surveillance: Algorithm and Flight Test Results , 2012, IEEE Transactions on Control Systems Technology.

[6]  Elias B. Kosmatopoulos,et al.  Distributed multi-robot coverage using micro aerial vehicles , 2013, 21st Mediterranean Conference on Control and Automation.

[7]  Antonio Barrientos,et al.  SwarmCity Project: Can an Aerial Swarm Monitor Traffic in a Smart City? , 2019, 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops).

[8]  Yaohong Qu,et al.  A UAV solution of regional surveillance based on pheromones and artificial potential field theory , 2015, 2015 International Conference on Unmanned Aircraft Systems (ICUAS).

[9]  Gigliola Vaglini,et al.  Swarm coordination of mini-UAVs for target search using imperfect sensors , 2018, Intell. Decis. Technol..

[10]  Vijay Kumar,et al.  Swarm Distribution and Deployment for Cooperative Surveillance by Micro-Aerial Vehicles , 2016, J. Intell. Robotic Syst..

[11]  S. Mohan,et al.  A review of research in multi-robot systems , 2012, 2012 IEEE 7th International Conference on Industrial and Information Systems (ICIIS).

[12]  Levent Bayındır,et al.  A review of swarm robotics tasks , 2016, Neurocomputing.

[13]  Antonio Barrientos Cruz,et al.  Comparison of heuristic algorithms in discrete search and surveillance tasks using aerial swarms , 2018 .

[14]  Fuhong Wang,et al.  Error analysis and accuracy assessment of GPS absolute velocity determination without SA , 2008 .

[15]  Erion Plaku,et al.  Reactive Motion Planning for Unmanned Aerial Surveillance of Risk-Sensitive Areas , 2015, IEEE Transactions on Automation Science and Engineering.

[16]  Erol Sahin,et al.  Swarm Robotics: From Sources of Inspiration to Domains of Application , 2004, Swarm Robotics.

[17]  Abdellah El Abbous,et al.  A modeling of GPS error distributions , 2017, 2017 European Navigation Conference (ENC).

[18]  Tamás Vicsek,et al.  Outdoor flocking and formation flight with autonomous aerial robots , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[19]  Derek James Bennet,et al.  Autonomous three-dimensional formation flight for a swarm of unmanned aerial vehicles , 2011 .

[20]  Aníbal Ollero,et al.  Cooperative Large Area Surveillance with a Team of Aerial Mobile Robots for Long Endurance Missions , 2013, J. Intell. Robotic Syst..

[21]  B. M. Albaker,et al.  A survey of collision avoidance approaches for unmanned aerial vehicles , 2009, 2009 International Conference for Technical Postgraduates (TECHPOS).

[22]  Wei Li,et al.  Persistent surveillance for a swarm of micro aerial vehicles by flocking algorithm , 2015 .