Visual Coverage Maintenance for Quadcopters Using Nonsmooth Barrier Functions

This paper presents a coverage control algorithm for teams of quadcopters with downward facing visual sensors that prevents the appearance of coverage holes in-between the monitored areas while maximizing the coverage quality as much as possible. We derive necessary and sufficient conditions for preventing the appearance of holes in-between the fields of views among trios of robots. Because this condition can be expressed as logically combined constraints, control nonsmooth barrier functions are implemented to enforce it. An algorithm which extends control nonsmooth barrier functions to hybrid systems is implemented to manage the switching among barrier functions caused by the changes of the robots composing trio. The performance and validity of the proposed algorithm are evaluated in simulation as well as on a team of quadcopters.

[1]  Sonia Martínez,et al.  Coverage control for mobile sensing networks , 2002, IEEE Transactions on Robotics and Automation.

[2]  Masayuki Fujita,et al.  Passivity-Based Control and Estimation in Networked Robotics , 2015 .

[3]  Wolfgang Straßer,et al.  Smart Camera Based Monitoring System and Its Application to Assisted Living , 2008, Proceedings of the IEEE.

[4]  Magnus Egerstedt,et al.  Boolean Composability of Constraints and Control Synthesis for Multi-Robot Systems via Nonsmooth Control Barrier Functions , 2018, 2018 IEEE Conference on Control Technology and Applications (CCTA).

[5]  Mohsen Guizani,et al.  Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges , 2018, IEEE Access.

[6]  Christos G. Cassandras,et al.  Sensor Networks and Cooperative Control , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[7]  Kamran Sayrafian-Pour,et al.  Distributed Deployment Algorithms for Efficient Coverage in a Network of Mobile Sensors With Nonidentical Sensing Capabilities , 2014, IEEE Transactions on Vehicular Technology.

[8]  Mac Schwager,et al.  Eyes in the Sky: Decentralized Control for the Deployment of Robotic Camera Networks , 2011, Proceedings of the IEEE.

[9]  Bernhard Rinner,et al.  An Introduction to Distributed Smart Cameras , 2008, Proceedings of the IEEE.

[10]  Francesco Bullo,et al.  Coordination and Geometric Optimization via Distributed Dynamical Systems , 2003, SIAM J. Control. Optim..

[11]  Saeid Nahavandi,et al.  Efficient Road Detection and Tracking for Unmanned Aerial Vehicle , 2015, IEEE Transactions on Intelligent Transportation Systems.

[12]  Jemal H. Abawajy,et al.  Coverage Hole Repair in WSNs Using Cascaded Neighbor Intervention , 2017, IEEE Sensors Journal.

[13]  Vijay Kumar,et al.  Minimum snap trajectory generation and control for quadrotors , 2011, 2011 IEEE International Conference on Robotics and Automation.

[14]  Magnus Egerstedt,et al.  Coverage Control for Multirobot Teams With Heterogeneous Sensing Capabilities , 2018, IEEE Robotics and Automation Letters.

[15]  Daniel E. Koditschek,et al.  Voronoi-Based Coverage Control of Pan/Tilt/Zoom Camera Networks , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

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

[17]  Gregory Galperin,et al.  A Tale of Three Circles , 2003 .

[18]  Masayuki Fujita,et al.  Experimental study of gradient-based visual coverage control on SO(3) toward moving object/human monitoring , 2015, 2015 American Control Conference (ACC).

[19]  Magnus Egerstedt,et al.  Hybrid Nonsmooth Barrier Functions With Applications to Provably Safe and Composable Collision Avoidance for Robotic Systems , 2019, IEEE Robotics and Automation Letters.

[20]  Anthony Tzes,et al.  Collaborative visual area coverage , 2017, Robotics Auton. Syst..

[21]  Amit K. Roy-Chowdhury,et al.  Distributed camera control via moving horizon Bayesian optimization , 2014, 2014 American Control Conference.

[22]  Masayuki Fujita,et al.  Visual Coverage Control for Teams of Quadcopters via Control Barrier Functions , 2019, 2019 International Conference on Robotics and Automation (ICRA).

[23]  Atsuyuki Okabe,et al.  Spatial Tessellations: Concepts and Applications of Voronoi Diagrams, Second Edition , 2000, Wiley Series in Probability and Mathematical Statistics.

[24]  Siddharth Mayya,et al.  Decentralized Minimum-Energy Coverage Control for Time-Varying Density Functions , 2019, 2019 International Symposium on Multi-Robot and Multi-Agent Systems (MRS).

[25]  José M. F. Moura,et al.  Understanding Traffic Density from Large-Scale Web Camera Data , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[26]  J. Cortés.  Discontinuous dynamical systems , 2008, IEEE Control Systems.

[27]  Xiaogang Wang,et al.  Intelligent multi-camera video surveillance: A review , 2013, Pattern Recognit. Lett..

[28]  Paulo Tabuada,et al.  Control Barrier Function Based Quadratic Programs for Safety Critical Systems , 2016, IEEE Transactions on Automatic Control.

[29]  Franz Aurenhammer,et al.  Power Diagrams: Properties, Algorithms and Applications , 1987, SIAM J. Comput..

[30]  Paul Thompson,et al.  Mapping and Tracking , 2009, IEEE Robotics & Automation Magazine.

[31]  F. Bullo,et al.  Motion Coordination with Distributed Information , 2007 .

[32]  S. Shankar Sastry,et al.  An Invitation to 3-D Vision: From Images to Geometric Models , 2003 .

[33]  Penggen Cheng,et al.  Unmanned aerial vehicle (UAV) real-time video registration for forest fire monitoring , 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..