Mapping a Polygon with Holes Using a Compass

We consider a simple robot inside a polygon \(\mathcal{P}\) with holes. The robot can move between vertices of \(\mathcal{P}\) along lines of sight. When sitting at a vertex, the robot observes the vertices visible from its current location, and it can use a compass to measure the angle of the boundary of \(\mathcal{P}\) towards north. The robot initially only knows an upper bound \(\bar{n}\) on the total number of vertices of \(\mathcal{P}\). We study the mapping problem in which the robot needs to infer the visibility graph G vis of \(\mathcal{P}\) and needs to localize itself within G vis. We show that the robot can always solve this mapping problem. To do this, we show that the minimum base graph of G vis is identical to G vis itself. This proves that the robot can solve the mapping problem, since knowing an upper bound on the number of vertices was previously shown to suffice for computing G vis.

[1]  Subir Kumar Ghosh,et al.  Visibility Algorithms in the Plane , 2007 .

[2]  Yann Disser,et al.  Reconstruction of a polygon from angles without prior knowledge of the size , 2010 .

[3]  F. Bullo,et al.  Distributed deployment of asynchronous guards in art galleries , 2006, 2006 American Control Conference.

[4]  Masafumi Yamashita,et al.  Distributed memoryless point convergence algorithm for mobile robots with limited visibility , 1999, IEEE Trans. Robotics Autom..

[5]  Steven M. LaValle,et al.  Mapping and Pursuit-Evasion Strategies For a Simple Wall-Following Robot , 2011, IEEE Transactions on Robotics.

[6]  Subhash Suri,et al.  Simple Robots in Polygonal Environments: A Hierarchy , 2008, ALGOSENSORS.

[7]  Haitao Wang,et al.  An improved algorithm for reconstructing a simple polygon from its visibility angles , 2012, Comput. Geom..

[8]  Subhash Suri,et al.  Simple Robots with Minimal Sensing: From Local Visibility to Global Geometry , 2007, Int. J. Robotics Res..

[9]  Subhash Suri,et al.  Reconstructing visibility graphs with simple robots , 2012, Theor. Comput. Sci..

[10]  Sebastiano Vigna,et al.  Fibrations of graphs , 2002, Discret. Math..

[11]  Bruce Randall Donald,et al.  On Information Invariants in Robotics , 1995, Artif. Intell..

[12]  Michael A. Bender,et al.  The power of a pebble: exploring and mapping directed graphs , 1998, STOC '98.

[13]  Jason M. O'Kane,et al.  Comparing the Power of Robots , 2008, Int. J. Robotics Res..

[14]  Jérémie Chalopin,et al.  Telling convex from reflex allows to map a polygon , 2011, STACS.

[15]  Jérémie Chalopin,et al.  How Simple Robots Benefit from Looking Back , 2010, CIAC.

[16]  Jérémie Chalopin,et al.  Mapping Simple Polygons: How Robots Benefit from Looking Back , 2011, Algorithmica.

[17]  Yann Disser,et al.  Reconstructing a Simple Polygon from Its Angles , 2010, SWAT.

[18]  Yann Disser,et al.  A polygon is determined by its angles , 2011, Comput. Geom..

[19]  Subhash Suri,et al.  Counting Targets with Mobile Sensors in an Unknown Environment , 2007, ALGOSENSORS.