Efficient complete coverage of a known arbitrary environment with applications to aerial operations

The problem of coverage of known space arises in a multitude of domains, including search and rescue, mapping, and surveillance. In many of these applications, it is desirable or even necessary for the solution to guarantee both the complete coverage of the free space, as well as the efficiency of the generated trajectory in terms of distance traveled. A novel algorithm is introduced, based on the boustrophedon cellular decomposition technique, for computing an efficient complete coverage path for a known environment populated with arbitrary obstacles. This hierarchical approach first partitions the space to be covered into non-overlapping cells, then solves the Chinese postman problem to compute an Eulerian circuit traversing through these cells, and finally concatenates per-cell seed spreader motion patterns into a complete coverage path. Practical considerations of the coverage system are also explored for operations with a non-holonomic aerial vehicle. The effects of various system parameters are evaluated in controlled environments using a high-fidelity flight simulator, in addition to over 200 km of in-field flight sessions with a fixed-wing unmanned aerial vehicle.

[1]  Howie Choset,et al.  Principles of Robot Motion: Theory, Algorithms, and Implementation ERRATA!!!! 1 , 2007 .

[2]  Elon Rimon,et al.  Spiral-STC: an on-line coverage algorithm of grid environments by a mobile robot , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[3]  Howie Choset,et al.  Coverage Path Planning: The Boustrophedon Cellular Decomposition , 1998 .

[4]  Joao P. Hespanha,et al.  Honey-pot constrained searching with local sensory information , 2006 .

[5]  Zhiyang Yao Finding Efficient Robot Path for the Complete Coverage of A Known Space , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[6]  B. Shirinzadeh,et al.  Optimal area covering using genetic algorithms , 2007, 2007 IEEE/ASME international conference on advanced intelligent mechatronics.

[7]  R. Forman Morse Theory for Cell Complexes , 1998 .

[8]  Vijay Kumar,et al.  An Optimization-Based Approach to Time-Critical Cooperative Surveillance and Coverage with UAVs , 2006, ISER.

[9]  Jack Edmonds,et al.  Matching, Euler tours and the Chinese postman , 1973, Math. Program..

[10]  Vladimir J. Lumelsky,et al.  Dynamic path planning in sensor-based terrain acquisition , 1990, IEEE Trans. Robotics Autom..

[11]  Er Meng Joo,et al.  Parallel region coverage using multiple UAVs , 2006, 2006 IEEE Aerospace Conference.

[12]  Masaki Hilaga,et al.  Topological Modeling for Visualization , 1997 .

[13]  George J. Pappas,et al.  Multi-UAV Cooperative Surveillance with Spatio-Temporal Specifications , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[14]  Ioannis M. Rekleitis,et al.  Optimal complete terrain coverage using an Unmanned Aerial Vehicle , 2011, 2011 IEEE International Conference on Robotics and Automation.

[15]  Philippe Pasquier,et al.  Complete and robust cooperative robot area coverage with limited range , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[16]  Mac Schwager,et al.  Unifying Geometric, Probabilistic, and Potential Field Approaches to Multi-robot Coverage Control , 2009, ISRR.

[17]  Hugh F. Durrant-Whyte,et al.  Recursive Bayesian search-and-tracking using coordinated uavs for lost targets , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[18]  Howie Choset,et al.  Coverage for robotics – A survey of recent results , 2001, Annals of Mathematics and Artificial Intelligence.

[19]  Howie Choset,et al.  Sensor Based Planing, Part II: Incremental COnstruction of the Generalized Voronoi Graph , 1995, ICRA.

[20]  Gaurav S. Sukhatme,et al.  Mobile Sensor Network Deployment using Potential Fields : A Distributed , Scalable Solution to the Area Coverage Problem , 2002 .

[21]  Sonal Jain,et al.  Multi-robot forest coverage , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[22]  Gregory Dudek,et al.  Multi-domain monitoring of marine environments using a heterogeneous robot team , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[23]  Eric Bonabeau,et al.  Swarm Intelligence: A New C2 Paradigm with an Application to Control Swarms of UAVs , 2003 .

[24]  Howie Choset,et al.  Path Planning for Robotic Demining: Robust Sensor-Based Coverage of Unstructured Environments and Probabilistic Methods , 2003, Int. J. Robotics Res..

[25]  Wesley H. Huang Optimal line-sweep-based decompositions for coverage algorithms , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[26]  A. Ollero,et al.  Multiple UAV cooperative searching operation using polygon area decomposition and efficient coverage algorithms , 2004, DARS.

[27]  Elon Rimon,et al.  Spanning-tree based coverage of continuous areas by a mobile robot , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[28]  Howie Choset,et al.  Sensor-based Coverage of Unknown Environments: Incremental Construction of Morse Decompositions , 2002, Int. J. Robotics Res..

[29]  Vijay Kumar,et al.  Time-optimal UAV trajectory planning for 3D urban structure coverage , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[30]  Howie Choset,et al.  Sensor based planning. II. Incremental construction of the generalized Voronoi graph , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[31]  Hyun Myung,et al.  Path Planning for Complete and Efficient Coverage Operation of Mobile Robots , 2007, 2007 International Conference on Mechatronics and Automation.

[32]  Gregory Dudek,et al.  Heuristic search planning to reduce exploration uncertainty , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[33]  Gregory Dudek,et al.  MARE: Marine Autonomous Robotic Explorer , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

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

[35]  Miri Weiss-Cohen,et al.  Lawn Mowing System for Known Areas , 2008, 2008 International Conference on Computational Intelligence for Modelling Control & Automation.

[36]  Zack J. Butler,et al.  CCR: A Complete Algorithm for Contact-Sensor Based Coverage of Rectilinear Environments , 1998 .

[37]  Ioannis M. Rekleitis,et al.  Optimal coverage of a known arbitrary environment , 2010, 2010 IEEE International Conference on Robotics and Automation.

[38]  Howie Choset,et al.  Morse Decompositions for Coverage Tasks , 2002, Int. J. Robotics Res..

[39]  Noa Agmon,et al.  The giving tree: constructing trees for efficient offline and online multi-robot coverage , 2008, Annals of Mathematics and Artificial Intelligence.

[40]  Gregory Dudek,et al.  A vision-based boundary following framework for aerial vehicles , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[41]  Peter Winkler,et al.  Note on Counting Eulerian Circuits , 2004, ArXiv.

[42]  Joel W. Burdick,et al.  A Coverage Algorithm for Multi-robot Boundary Inspection , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[43]  Howie Choset,et al.  Coverage of Known Spaces: The Boustrophedon Cellular Decomposition , 2000, Auton. Robots.

[44]  Vijay Kumar,et al.  An Optimization-based Approach to Time Critical Cooperative Surveillance and Coverage with Unmanned Aerial Vehicles , 2006 .

[45]  Howie Choset,et al.  Efficient Boustrophedon Multi-Robot Coverage: an algorithmic approach , 2008, Annals of Mathematics and Artificial Intelligence.

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

[47]  Gregory Dudek,et al.  Multi-robot collaboration for robust exploration , 2004, Annals of Mathematics and Artificial Intelligence.

[48]  Liam Paull,et al.  An information gain based adaptive path planning method for an autonomous underwater vehicle using sidescan sonar , 2010, 2010 IEEE International Conference on Automation Science and Engineering.