Detecting and Tracking Level Sets of Scalar Fields using a Robotic Sensor Network

We introduce an algorithm which detects and traces a specified level set of a scalar field (a contour) on a plane. A network of static sensor nodes with limited communication and processing are deployed in a planar environment along with a mobile node which can both sense and move. As the mobile node moves through the environment, it computes the local spatial gradient of the field by communicating with its immediate neighbors in the static sensor network. The algorithm causes the mobile node to perform gradient descent on the scalar field till it arrives at a location on the desired contour. From this point onwards, the algorithm drives the mobile node to trace the desired contour without departing from it. Experiments in simulation indicate that the required contour is found with reasonable accuracy (between 80-90%) for networks with node degree of greater than or equal to six. Our results also indicate that the paths generated by our algorithm are near-optimal in terms of the distance traversed by the mobile node. Our preliminary experimental results with a physical robot show that our algorithm is feasible.

[1]  EstrinDeborah,et al.  Connecting the Physical World with Pervasive Networks , 2002 .

[2]  Gaurav S. Sukhatme,et al.  Connecting the Physical World with Pervasive Networks , 2002, IEEE Pervasive Comput..

[3]  Deborah Estrin,et al.  Coping with irregular spatio-temporal sampling in sensor networks , 2004, CCRV.

[4]  Satish Kumar,et al.  Next century challenges: scalable coordination in sensor networks , 1999, MobiCom.

[5]  Gaurav S. Sukhatme,et al.  Proposed approach for combining distributed sensing, robotic sampling, and offline analysis for in-situ marine monitoring , 2001, SPIE Optics East.

[6]  John Anderson,et al.  An analysis of a large scale habitat monitoring application , 2004, SenSys '04.

[7]  Deborah Estrin,et al.  Self-configuring localization systems: Design and Experimental Evaluation , 2004, TECS.

[8]  Robert Szewczyk,et al.  System architecture directions for networked sensors , 2000, ASPLOS IX.

[9]  Gaurav S. Sukhatme,et al.  A Testbed for Experiments with Sensor/Actuator Networks , 2002 .

[10]  Ramesh Govindan,et al.  Localized edge detection in sensor fields , 2003, Ad Hoc Networks.

[11]  Gaurav S. Sukhatme,et al.  Robomote: enabling mobility in sensor networks , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[12]  Panganamala Ramana Kumar,et al.  The Number of Neighbors Needed for Connectivity of Wireless Networks , 2004, Wirel. Networks.

[13]  Urbashi Mitra,et al.  Boundary Estimation in Sensor Networks: Theory and Methods , 2003, IPSN.

[14]  Leonidas J. Guibas,et al.  A dual-space approach to tracking and sensor management in wireless sensor networks , 2002, WSNA '02.

[15]  Howie Choset,et al.  Sensor based planning: a control law for generating the generalized Voronoi graph , 1997, 1997 8th International Conference on Advanced Robotics. Proceedings. ICAR'97.

[16]  Mac Schwager,et al.  Distributed Coverage Control with Sensory Feedback for Networked Robots , 2006, Robotics: Science and Systems.