W
William J. Kaiser
Researcher at University of California
Publications - 61
Citations - 2490
William J. Kaiser is an academic researcher from University of California. The author has contributed to research in topics: Wireless sensor network & Robot. The author has an hindex of 24, co-authored 61 publications receiving 2405 citations. Previous affiliations of William J. Kaiser include University of California, Los Angeles.
Papers
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Journal ArticleDOI
Efficient informative sensing using multiple robots
TL;DR: ESIP (efficient Single-robot Informative Path planning), an approximation algorithm for optimizing the path of a single robot, and a general technique, sequential allocation, which can be used to extend any single robot planning algorithm, such as eSIP, for the multi-ro robot problem.
Patent
Cmos integrated microsensor with a precision measurement circuit
TL;DR: In this article, a nulling feedback voltage is used to maintain the switch DC voltage across sensing capacitors in a null condition and to maintain high sensitivity without requiring either a precision transformer or regulated power sources in the capacitance bridge of the accelerometer.
Journal Article
Call and Response: Experiments in Sampling the Environment
Maxim A. Batalin,Mohammad Rahimi,Yan Yu,Duo Liu,Aman Kansal,Gaurav S. Sukhatme,William J. Kaiser,Mark Hansen,Gregory J. Pottie,Mani Srivastava,Deborah Estrin +10 more
TL;DR: In this article, the authors describe an embedded networked sensor architecture that merges sensing and articulation with adaptive algorithms that are responsive to both variability in environmental phenomena discovered by the mobile sensors and to discrete events discovered by static sensors.
Proceedings ArticleDOI
Call and response: experiments in sampling the environment
Maxim A. Batalin,Mohammad Rahimi,Yan Yu,Duo Liu,Aman Kansal,Gaurav S. Sukhatme,William J. Kaiser,Mark Hansen,Gregory J. Pottie,Mani Srivastava,Deborah Estrin +10 more
TL;DR: In this paper, an embedded networked sensor architecture that merges sensing and articulation with adaptive algorithms that are responsive to both variabilityin environmental phenomena discovered bythe mobile sensors and to discrete events discovered byst atic sensors is presented.
Journal Article
Adaptive Sampling for Environmental Robotics
Mohammad Rahimi,Richard Pon,Deborah Estrin,William J. Kaiser,Mani Srivastava,Gaurav S. Sukhatme +5 more
TL;DR: This paper introduces a new approach of mobile node adaptive sampling with the objective of minimizing error between the actual and reconstructed spatiotemporal behavior of environmental variables while minimizing required motion in NIMS environmental robotics.