Visual Coverage Control for Teams of Quadcopters via Control Barrier Functions

This paper presents a coverage control strategy for teams of quadcopters that ensures that no area is left unsurveyed in between the fields of view of the visual sensors mounted on the quadcopters. We present a locational cost that quantifies the team’s coverage performance according to the sensors’ performance function. Moreover, the cost function penalizes overlaps between the fields of view of the different sensors, with the objective of increasing the area covered by the team. A distributed control law is derived for the quadcopters so that they adjust their position and zoom according to the direction of ascent of the cost. Control barrier functions are implemented to ensure that, while executing the gradient ascent control law, no holes appear in between the fields of view of neighboring robots. The performance of the algorithm is evaluated in simulated experiments.

[1]  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).

[2]  Paulo Tabuada,et al.  Robustness of Control Barrier Functions for Safety Critical Control , 2016, ADHS.

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

[4]  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..

[5]  Vin de Silva,et al.  Coordinate-free Coverage in Sensor Networks with Controlled Boundaries via Homology , 2006, Int. J. Robotics Res..

[6]  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.

[7]  Abubakr Muhammad,et al.  Coverage and hole-detection in sensor networks via homology , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

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

[9]  Philip M. Dames,et al.  Distributed multi-target search and tracking using the PHD filter , 2017, 2017 International Symposium on Multi-Robot and Multi-Agent Systems (MRS).

[10]  Qiang Du,et al.  Centroidal Voronoi Tessellations: Applications and Algorithms , 1999, SIAM Rev..

[11]  Christos G. Cassandras,et al.  Sensor Networks and Cooperative Control , 2005, CDC 2005.

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

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

[14]  Mac Schwager,et al.  Adapting to sensing and actuation variations in multi-robot coverage , 2017, Int. J. Robotics Res..

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

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

[17]  Magnus Egerstedt,et al.  Graph Theoretic Methods in Multiagent Networks , 2010, Princeton Series in Applied Mathematics.

[18]  Sreela Sasi,et al.  Automated Surveillance of Unattended Bags for Complex Situations , 2009, 2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies.

[19]  Prasan Kumar Sahoo,et al.  An Efficient Distributed Coverage Hole Detection Protocol for Wireless Sensor Networks , 2016, Sensors.

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

[21]  S. Shankar Sastry,et al.  An Invitation to 3-D Vision , 2004 .

[22]  Amit K. Roy-Chowdhury,et al.  Distributed Constrained Optimization for Bayesian Opportunistic Visual Sensing , 2014, IEEE Transactions on Control Systems Technology.

[23]  Tarak Gandhi,et al.  Distributed interactive video arrays for event capture and enhanced situational awareness , 2005, IEEE Intelligent Systems.

[24]  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).

[25]  S. Sitharama Iyengar,et al.  Coverage Assessment and Target Tracking in 3D Domains , 2011, Sensors.

[26]  Suman Srinivasan,et al.  Airborne traffic surveillance systems: video surveillance of highway traffic , 2004, VSSN '04.

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

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

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

[30]  Guangjie Han,et al.  A survey on coverage and connectivity issues in wireless sensor networks , 2012, J. Netw. Comput. Appl..

[31]  Syed Abdurrahman Smart video-based surveillance: Opportunities and challenges from image processing perspectives , 2016, 2016 3rd International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE).

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