Sensor Resource Management driven by threat projection and priorities

Anderson, Joseph; Liu, Hong

doi:10.1016/j.ins.2007.11.029

Cited by 7 publications

(2 citation statements)

References 16 publications

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“…Using the corrected acceleration solution, the variance is larger and the value is more dispersed, the angle difference variance is larger, so this algorithm is not desirable [10]. The absolute value of the error between the first-order complementary filter and the second-order complementary filter and the reference data is the smallest and the variance is smaller and the data is more concentrated, and the variance is small and the data are concentrated.…”

Section: The Experimental Resultsmentioning

confidence: 99%

Application of Multi-order Complementary Filtering Technique in Dynamic Attitude Measurement of Forestry Special Robots

Liu¹,

Ren²,

Deng³

2017

Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)

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Abstract-The wide application foreground of forestry special robots makes it become the hotspot of current research. The attitude angle measurement [1] of the special crawler-type robot is one of the key problems. Based on the complementary filtering algorithm, the attitude and angle measuring circuit and data processing algorithm of the special crawler robot are designed. The signal filtering and preprocessing are used to combine the two sensor data. The calculation method of the key parameters in the complementary filtering algorithm is analyzed. The method is applied to the angle measurement of the special crawler robot, and the verification test is carried out. And the experiment result shows that this experiment method is applicable to forestry robots.Keywords-forestry special robots; multi-order complementary filtering; integral drift; attitude solving I. INTRODUCTION Attitude angle measurement is a prerequisite for the operation and control of special crawler-type robots. The accuracy and speed of the attitude angle measurement [2] will directly affect the stability and reliability of the control algorithm of the special crawler robot. With the miniaturization of the inertial measurement components and the improvement of the computing power of the microprocessors, the low-cost inertial measurement unit (IMU) is widely used in posture measurement of forestry special crawler-type robots, and high accuracy attitude measurement is realized by combining the microprocessor data processing algorithms. IMU is mainly composed of low cost MEMS gyroscope and three axis accelerometer. MEMS gyroscope has good autonomy [3], low power consumption, good mechanical and electrical performance advantages of integration. However, the MEMS gyroscope has the characteristic of temperature drift; the measurement error will be accumulated with the accumulation of time, thus affecting the measurement accuracy. The accelerometer will be affected by the vibration of the robot, aliasing the additional amount of vibration interference. So a single sensor measurement is difficult to get accurate attitude angle.

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Section: The Experimental Resultsmentioning

confidence: 99%

Application of Multi-order Complementary Filtering Technique in Dynamic Attitude Measurement of Forestry Special Robots

Liu¹,

Ren²,

Deng³

2017

Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)

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“…In particular, radio communication (transmission and reception) is the primary source of energy consumption in sensor networks [19], minimizing radio communication in query execution can save large amounts of energy and thereby prolonging the network lifetime significantly. Several studies on different query optimization in sensor networks have been conducted recently [21,10,2].…”

Section: Introductionmentioning

confidence: 99%

Top-k query evaluation in sensor networks under query response time constraint

Liang

Chen

2011

Information Sciences

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a b s t r a c tTop-k query in a wireless sensor network is to find the k sensor nodes with the highest sensing values. To evaluate the top-k query in such an energy-constrained network poses great challenges, due to the unique characteristics imposed on its sensors. Existing solutions for top-k query in the literature mainly focused on energy efficiency but little attention has been paid to the query response time and its effect on the network lifetime. In this paper we address the query response time and its effect on the network lifetime through the study of the top-k query problem in sensor networks with the response time constraint. We aim at finding an energy-efficient routing tree and evaluating top-k queries on the tree such that the network lifetime is significantly prolonged, provided that the query response time constraint is met too. To do so, we first present a cost model of energy consumption for answering top-k queries and introduce the query response time definition. We then propose a novel joint query optimization framework, which consists of finding a routing tree in the network and devising a filter-based evaluation algorithm for top-k query evaluation on the tree. We finally conduct extensive experiments by simulation to evaluate the performance of the proposed algorithms, in terms of the total energy consumption, the maximum energy consumption among nodes, the query response time, and the network lifetime. The experimental results showed that there is a non-trivial tradeoff between the query response time and the network lifetime, and the joint query optimization framework can prolong the network lifetime significantly under a specified query response time constraint.

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Learning-based airborne sensor task assignment in unknown dynamic environments

Wang

Liang

et al. 2022

Engineering Applications of Artificial Intelligence

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Sensor Resource Management driven by threat projection and priorities

Cited by 7 publications

References 16 publications

Application of Multi-order Complementary Filtering Technique in Dynamic Attitude Measurement of Forestry Special Robots

Application of Multi-order Complementary Filtering Technique in Dynamic Attitude Measurement of Forestry Special Robots

Top-k query evaluation in sensor networks under query response time constraint

Learning-based airborne sensor task assignment in unknown dynamic environments

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