TY - GEN
T1 - Effective control for wireless sensor and mobile actuator network in regulation of environmental density function
AU - Lin, Mu Tai
AU - Liu, Yen Chen
N1 - Funding Information:
This work was partially supported by the Ministry of Science and Technology, Taiwan, under grants MOST 105-2221-E-006-160-MY3 and MOST 106-2221-E-006-010-MY3.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/30
Y1 - 2018/8/30
N2 - This paper proposes an environmental regulating system by using a multi-robot system in cooperation with wireless sensor networks. Wireless sensors pre-deployed in the environment and embedded in mobile robots can gather sensory information to estimate the distribution of environmental variable. The environment distribution is illustrated by a density function which is constructed by Gaussian mixture model based on Expectation Maximization (EM) algorithm to estimate real condition. Subsequently, a gradient decent coverage control is proposed to drive the multi-robot system to cover the optimal distribution based on the estimated density function. Meanwhile, the actuators embedded on mobile robots are designed to regulate the environment to achieve a desired value of density function. Numerical examples are illustrated to show the performance of the proposed control system.
AB - This paper proposes an environmental regulating system by using a multi-robot system in cooperation with wireless sensor networks. Wireless sensors pre-deployed in the environment and embedded in mobile robots can gather sensory information to estimate the distribution of environmental variable. The environment distribution is illustrated by a density function which is constructed by Gaussian mixture model based on Expectation Maximization (EM) algorithm to estimate real condition. Subsequently, a gradient decent coverage control is proposed to drive the multi-robot system to cover the optimal distribution based on the estimated density function. Meanwhile, the actuators embedded on mobile robots are designed to regulate the environment to achieve a desired value of density function. Numerical examples are illustrated to show the performance of the proposed control system.
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U2 - 10.1109/AIM.2018.8452364
DO - 10.1109/AIM.2018.8452364
M3 - Conference contribution
AN - SCOPUS:85053889345
SN - 9781538618547
T3 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
SP - 1190
EP - 1195
BT - AIM 2018 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2018
Y2 - 9 July 2018 through 12 July 2018
ER -