TY - GEN

T1 - K-robots clustering of moving sensors using coresets

AU - Feldman, Dan

AU - Gil, Stephanie

AU - Knepper, Ross A.

AU - Julian, Brian

AU - Rus, Daniela

PY - 2013

Y1 - 2013

N2 - We present an approach to position k servers (e.g. mobile robots) to provide a service to n independently moving clients; for example, in mobile ad-hoc networking applications where inter-agent distances need to be minimized, connectivity constraints exist between servers, and no a priori knowledge of the clients' motion can be assumed. Our primary contribution is an algorithm to compute and maintain a small representative set, called a kinematic coreset, of the n moving clients.We prove that, in any given moment, the maximum distance between the clients and any set of k servers is approximated by the coreset up to a factor of (1 ± ε), where ε > 0 is an arbitrarily small constant. We prove that both the size of our coreset and its update time is polynomial in k log(n)/ε. Although our optimization problem is NP-hard (i.e., takes time exponential in the number of servers to solve), solving it on the small coreset instead of the original clients results in a tractable controller. The approach is validated in a small scale hardware experiment using robot servers and human clients, and in a large scale numerical simulation using thousands of clients.

AB - We present an approach to position k servers (e.g. mobile robots) to provide a service to n independently moving clients; for example, in mobile ad-hoc networking applications where inter-agent distances need to be minimized, connectivity constraints exist between servers, and no a priori knowledge of the clients' motion can be assumed. Our primary contribution is an algorithm to compute and maintain a small representative set, called a kinematic coreset, of the n moving clients.We prove that, in any given moment, the maximum distance between the clients and any set of k servers is approximated by the coreset up to a factor of (1 ± ε), where ε > 0 is an arbitrarily small constant. We prove that both the size of our coreset and its update time is polynomial in k log(n)/ε. Although our optimization problem is NP-hard (i.e., takes time exponential in the number of servers to solve), solving it on the small coreset instead of the original clients results in a tractable controller. The approach is validated in a small scale hardware experiment using robot servers and human clients, and in a large scale numerical simulation using thousands of clients.

UR - http://www.scopus.com/inward/record.url?scp=84887303351&partnerID=8YFLogxK

U2 - 10.1109/ICRA.2013.6630677

DO - 10.1109/ICRA.2013.6630677

M3 - Conference contribution

AN - SCOPUS:84887303351

SN - 9781467356411

T3 - Proceedings - IEEE International Conference on Robotics and Automation

SP - 881

EP - 888

BT - 2013 IEEE International Conference on Robotics and Automation, ICRA 2013

T2 - 2013 IEEE International Conference on Robotics and Automation, ICRA 2013

Y2 - 6 May 2013 through 10 May 2013

ER -