TY - GEN
T1 - Fleet size of multi-robot systems for exploration of structured environments
AU - Cabrera-Mora, Flavio
AU - Xiao, Jizhong
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/10/31
Y1 - 2014/10/31
N2 - The fleet size of a multi-robot system is an important parameter to be considered for real robotics applications since it will determine the cost and the time of execution of any given task. Unfortunately, it is a topic that has received little attention in the robotics literature. The study of the fleet size will allow for the design and implementation of more effective techniques and coordination methods for multi-robot systems. In this paper we study the effects of the fleet size on the time of exploration of a structured environment. We present an analysis that allows us to specify the maximum fleet size that provides the maximum reduction on the exploration time when the structured environment is modeled as a tree. The analysis is applied to the Multi-Robot Depth First Search (MR-DFS) algorithm that allows for maximum parallelism when an exploration process starts from a single point. The analysis provides an expression for the average time of exploration of a tree and for the maximum number of robots that produces a significant reduction on the exploration time.
AB - The fleet size of a multi-robot system is an important parameter to be considered for real robotics applications since it will determine the cost and the time of execution of any given task. Unfortunately, it is a topic that has received little attention in the robotics literature. The study of the fleet size will allow for the design and implementation of more effective techniques and coordination methods for multi-robot systems. In this paper we study the effects of the fleet size on the time of exploration of a structured environment. We present an analysis that allows us to specify the maximum fleet size that provides the maximum reduction on the exploration time when the structured environment is modeled as a tree. The analysis is applied to the Multi-Robot Depth First Search (MR-DFS) algorithm that allows for maximum parallelism when an exploration process starts from a single point. The analysis provides an expression for the average time of exploration of a tree and for the maximum number of robots that produces a significant reduction on the exploration time.
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U2 - 10.1109/IROS.2014.6942586
DO - 10.1109/IROS.2014.6942586
M3 - Conference contribution
AN - SCOPUS:84911469474
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 370
EP - 375
BT - IROS 2014 Conference Digest - IEEE/RSJ International Conference on Intelligent Robots and Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014
Y2 - 14 September 2014 through 18 September 2014
ER -