Robust Adaptive Signal Processing With Robotics
Waleed Mohammed Nabeel Mohammed Sadek;
Abstract
Filtering data in real-time requires dedicated hardware to meet demanding time requirements. If the statistics of the signal are not known, then adaptive filtering algorithms can be implemented to estimate the signals statistics iteratively.
Most sensors used in robotics are subject to a great deal of interference, variation, and changing results due to the ever-changing environmental conditions. As a result, many people become rather frustrated that the results from the sensors change and give occasional false readings so that Robotic sensors needed to design efficient filtering structures. Furthermore, some manufacturers now include complete microprocessors within the robotic sensor fabric. This mix of hardware and embedded software on a single chip is ideal for fast filter structures with arithmetic intensive adaptive algorithms.
Thesis aims to design an adaptive sensor used in robotic systems at normal or difficult environmental conditions at which the signal to noise ratio has small values, by applying an efficient adaptive filtering algorithm on the sensor to minimize the
. effect of the environmental noises and so enhances the robot performance.
The first task of the present work, design three adaptive filtering algorithms which are widely used in most applications especially in robotics systems,-the least mean-square (LMS) (Variable step-size LMS and Fixed step-size LMS) and the recursive-least-squares (RLS) algorithm, and then testing their performance by how each one of them can minimize the effect of noise signals that added to the desired signal at the input of the filter and present the factors that influence that performance.
The second task, application of the adaptive filtering algorithms on one type of the sensors that is mostly used in robotic systems (ultrasonic range finder .sensoi') and test weather they can be efficient for making adaptive sensor model.
The third task, make a comparison between the performance of the adaptive filtering algorithms for the first and the second tasks.
Finally we will end up with the conclusion and the future work.
Most sensors used in robotics are subject to a great deal of interference, variation, and changing results due to the ever-changing environmental conditions. As a result, many people become rather frustrated that the results from the sensors change and give occasional false readings so that Robotic sensors needed to design efficient filtering structures. Furthermore, some manufacturers now include complete microprocessors within the robotic sensor fabric. This mix of hardware and embedded software on a single chip is ideal for fast filter structures with arithmetic intensive adaptive algorithms.
Thesis aims to design an adaptive sensor used in robotic systems at normal or difficult environmental conditions at which the signal to noise ratio has small values, by applying an efficient adaptive filtering algorithm on the sensor to minimize the
. effect of the environmental noises and so enhances the robot performance.
The first task of the present work, design three adaptive filtering algorithms which are widely used in most applications especially in robotics systems,-the least mean-square (LMS) (Variable step-size LMS and Fixed step-size LMS) and the recursive-least-squares (RLS) algorithm, and then testing their performance by how each one of them can minimize the effect of noise signals that added to the desired signal at the input of the filter and present the factors that influence that performance.
The second task, application of the adaptive filtering algorithms on one type of the sensors that is mostly used in robotic systems (ultrasonic range finder .sensoi') and test weather they can be efficient for making adaptive sensor model.
The third task, make a comparison between the performance of the adaptive filtering algorithms for the first and the second tasks.
Finally we will end up with the conclusion and the future work.
Other data
| Title | Robust Adaptive Signal Processing With Robotics | Other Titles | المعالجة التكيفية المحكمة لبيانات الروبوت | Authors | Waleed Mohammed Nabeel Mohammed Sadek | Issue Date | 2006 |
Attached Files
| File | Size | Format | |
|---|---|---|---|
| B12763.pdf | 1.01 MB | Adobe PDF | View/Open |
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