29-08-2010, 08:19 AM
Need the abstract of the project...
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INTELLIGENT MOBILE ROBOT NAVIGATION TECHNOLOGY USING RFID
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18-09-2010, 03:00 PM
More Info About INTELLIGENT MOBILE ROBOT NAVIGATION TECHNOLOGY USING RFID
for brief explanatioon about INTELLIGENT MOBILE ROBOT NAVIGATION TECHNOLOGY USING RFID
An Intelligent Mobile Robot Navigation Technique Using RFID Technology - Presentation Transcript
An Intelligent Mobile Robot Navigation Technique Using RFID Technology
Reference ï® Gueaieb, W. Miah, M.S. “An Intelligent Mobile Robot Navigation Technique Using RFID Technology†Instrumentation and Measurement, IEEE Transactions on , Sept. 2008
Outline ï® Introduction ï® Related Work ï® RFID Systems ï® Proposed Approach ï® Experimental Results ï® Conclusion
Introduction (1/2) ï® MOBILE robot navigation has stood as an open and challenging problem over the last few decades ï® Most of the robot navigation algorithms proposed in the literature are either tailored toward particular structured environments or driven by an overwhelming degree of computational complexity. in some cases, the hardware needed to implement the algorithm can be more costly than the robot itself
Introduction (2/2) ï® The proposed algorithm takes advantage of the emerging Radio Frequency IDentiï¬cation (RFID) technology and a fuzzy logic controller (FLC) to guide the robot to navigate in its working space ï® This navigation method is based on continuous encoder readings that provide the position, orientation, and linear and angular velocities of the robot ï® Although several modules are involved in operating mobile platforms, such as, for example, the localization, navigation, obstacle detection, obstacle avoidance, and path planning modules, only the former two are considered here.
Related Work (1/2) ï® The indoor mobile robot navigation presented in [6] uses a global ultrasonic system for the robot’s position estimation while navigating in an environment ï® Hallmann and Siemiatkowska developed a mobile robot B14 to navigate in a partially known environment ï® Betge-Brezetz et al. focused on the high-level representation of the natural scene to guide a mobile robot in an a priori unknown environment ï® Wijk and Christensen developed a algorithm for natural landmark extraction from sonar data streamed from a mobile platform
Related Work (2/2) ï® Khubitz et al. presented a navigation system that uses RFID tags as artiï¬cial landmarks ï® Tsukiyama [20], where the robot tries to build a topological map of its surround- ing environment to be used in path planning and navigation ï® Chae et al. proposed a mobile robot localization method with the help of a combination of RFID and vision technologies
RFID Systems (1/2)
RFID Systems (2/2) ï® In this paper, we are particularly interested in the phase of the baseband signal received at the reader’s end as a result of the tag’s response. ï® This phase φ is derived from the in-phase (I) and quadrature (Q) components of the received signal ï®
Proposed Approach ï® The general high-level architecture for the proposed navigation system consists of an RFID communication module and an FLC, in addition to the software performing data processing and computing the necessary control actions ï°A. RFID Communication Module ï°B. FLC ï°C. Navigation Algorithm
Proposed Approach
RFID Communication Module ï® Interested in the signal broadcasted by the tag representing the robot’s destination at that time instant ï® Let φ1 and φ2 be the phase angles of the signal received by the reader’s reception antennas 1 and 2 ï® ï® However, that none of the commercially available RFID readers to date is capable of providing the necessary information to perform these calculations ï® Using a custom- made RFID reader and a digital oscilloscope to conï¬rm the fact that the phase difference deï¬ned in (2)
RFID system setup to compute the phase difference
FLC ï® The aim of the FLC is to decide on the amount of tune- up ∆θ that the robot has to apply to its direction θ to converge to its target position ï®
FLC’s membership functions (a) Input membership functions (b) Output membership functions (not to scale)
Navigation Algorithm ï® A navigation algorithm is needed to act as a supervisory control layer to process and coordinate the efforts of the RFID communication module and the FLC on one hand and to pass the FLC’s output control actions to the robot’s relevant actua- tors on the other hand
Experimental Results ï® A. Following a Line Segment ï® B. Following a Complex Path ï® C. Following a Hallway
ï® Experimental setup for following a line segment
Proposed algorithm’s performance in following a line segment (an initial orientation of 90◦)
Proposed algorithm’s performance in following a line segment (an initial orientation of 0◦)
ï® Experimental setup for following a complex path
Proposed algorithm’s performance in following a complex path with acute angles
Experimental setup for hallway following (not to scale)
Proposed algorithm’s performance in following a hallway
Conclusion ï® The algorithm can guide the robot to under any RFID tag by a simple intelligent processing of the phase difference of the signal sent by the tag and received at both antennas of the RFID reader mounted on the robot ï® A new class of robot navigation techniques that are simple, computationally cost effective, and modular in the sense that they are independent of any speciï¬c robot architecture
refered by http://slidesharewacerone/an-intelligent-mobile-robot-navigation-technique-using-rfid-technology-presentation
for brief explanatioon about INTELLIGENT MOBILE ROBOT NAVIGATION TECHNOLOGY USING RFID
An Intelligent Mobile Robot Navigation Technique Using RFID Technology - Presentation Transcript
An Intelligent Mobile Robot Navigation Technique Using RFID Technology
Reference ï® Gueaieb, W. Miah, M.S. “An Intelligent Mobile Robot Navigation Technique Using RFID Technology†Instrumentation and Measurement, IEEE Transactions on , Sept. 2008
Outline ï® Introduction ï® Related Work ï® RFID Systems ï® Proposed Approach ï® Experimental Results ï® Conclusion
Introduction (1/2) ï® MOBILE robot navigation has stood as an open and challenging problem over the last few decades ï® Most of the robot navigation algorithms proposed in the literature are either tailored toward particular structured environments or driven by an overwhelming degree of computational complexity. in some cases, the hardware needed to implement the algorithm can be more costly than the robot itself
Introduction (2/2) ï® The proposed algorithm takes advantage of the emerging Radio Frequency IDentiï¬cation (RFID) technology and a fuzzy logic controller (FLC) to guide the robot to navigate in its working space ï® This navigation method is based on continuous encoder readings that provide the position, orientation, and linear and angular velocities of the robot ï® Although several modules are involved in operating mobile platforms, such as, for example, the localization, navigation, obstacle detection, obstacle avoidance, and path planning modules, only the former two are considered here.
Related Work (1/2) ï® The indoor mobile robot navigation presented in [6] uses a global ultrasonic system for the robot’s position estimation while navigating in an environment ï® Hallmann and Siemiatkowska developed a mobile robot B14 to navigate in a partially known environment ï® Betge-Brezetz et al. focused on the high-level representation of the natural scene to guide a mobile robot in an a priori unknown environment ï® Wijk and Christensen developed a algorithm for natural landmark extraction from sonar data streamed from a mobile platform
Related Work (2/2) ï® Khubitz et al. presented a navigation system that uses RFID tags as artiï¬cial landmarks ï® Tsukiyama [20], where the robot tries to build a topological map of its surround- ing environment to be used in path planning and navigation ï® Chae et al. proposed a mobile robot localization method with the help of a combination of RFID and vision technologies
RFID Systems (1/2)
RFID Systems (2/2) ï® In this paper, we are particularly interested in the phase of the baseband signal received at the reader’s end as a result of the tag’s response. ï® This phase φ is derived from the in-phase (I) and quadrature (Q) components of the received signal ï®
Proposed Approach ï® The general high-level architecture for the proposed navigation system consists of an RFID communication module and an FLC, in addition to the software performing data processing and computing the necessary control actions ï°A. RFID Communication Module ï°B. FLC ï°C. Navigation Algorithm
Proposed Approach
RFID Communication Module ï® Interested in the signal broadcasted by the tag representing the robot’s destination at that time instant ï® Let φ1 and φ2 be the phase angles of the signal received by the reader’s reception antennas 1 and 2 ï® ï® However, that none of the commercially available RFID readers to date is capable of providing the necessary information to perform these calculations ï® Using a custom- made RFID reader and a digital oscilloscope to conï¬rm the fact that the phase difference deï¬ned in (2)
RFID system setup to compute the phase difference
FLC ï® The aim of the FLC is to decide on the amount of tune- up ∆θ that the robot has to apply to its direction θ to converge to its target position ï®
FLC’s membership functions (a) Input membership functions (b) Output membership functions (not to scale)
Navigation Algorithm ï® A navigation algorithm is needed to act as a supervisory control layer to process and coordinate the efforts of the RFID communication module and the FLC on one hand and to pass the FLC’s output control actions to the robot’s relevant actua- tors on the other hand
Experimental Results ï® A. Following a Line Segment ï® B. Following a Complex Path ï® C. Following a Hallway
ï® Experimental setup for following a line segment
Proposed algorithm’s performance in following a line segment (an initial orientation of 90◦)
Proposed algorithm’s performance in following a line segment (an initial orientation of 0◦)
ï® Experimental setup for following a complex path
Proposed algorithm’s performance in following a complex path with acute angles
Experimental setup for hallway following (not to scale)
Proposed algorithm’s performance in following a hallway
Conclusion ï® The algorithm can guide the robot to under any RFID tag by a simple intelligent processing of the phase difference of the signal sent by the tag and received at both antennas of the RFID reader mounted on the robot ï® A new class of robot navigation techniques that are simple, computationally cost effective, and modular in the sense that they are independent of any speciï¬c robot architecture
refered by http://slidesharewacerone/an-intelligent-mobile-robot-navigation-technique-using-rfid-technology-presentation
13-10-2010, 10:55 AM
[attachment=5814]
ABSTRACT:
A voice based system has been developed to control a mobile robot using oral
Commands .the system is divided into two man components
peech recognition engine and robotic control unit.in the speech recognition engine,hidden markov models are used
As main method in recognizing oral commands.the robotic control unit is developed under the ARIA environment ,which is provide by the robot manufacturer.
We are taking the voice data from the microphone using a soundcard.this data is stored
In an array.this earray is passed on to a function which extracts word from the array(i.e.
Spoken words are extracted & quiet periods are dumped).these words are sent to a function which extracts frequency as a function of time.this frequency vector of the spoken word.this vector is compared with reference vectors.one of the reference vectors would match(i.e. the inner product in this case greater than the other 5).the command correspondingto this reference vector is fed to the microcontroller.
In this project we are getting a user dependent isolated word recognition system with a recognition accuracy of about 85% using 6 words the accuracy can be improved further
And the system can be used for more number of word if during the trainingof the systemo
The noise conditions are improved
Applications:
We belive such a system would find wide variety of applications menu driven systems such as email readers household appliances like washing machines microwave ovens
And pagers and mobiles e.t.c will become voice controlled in future our project may find applications out their because inherently the number of possible inputs is limited using our soft ware these can be controlled through a network as well
OPERATOR INTERFACE FOR DIRECTION CONTROL USING AN INTELLIGENT
ROBOT BASED ON VOICE DETECTION SYSTEM
ROBOT BASED ON VOICE DETECTION SYSTEM
ABSTRACT:
A voice based system has been developed to control a mobile robot using oral
Commands .the system is divided into two man components
peech recognition engine and robotic control unit.in the speech recognition engine,hidden markov models are usedAs main method in recognizing oral commands.the robotic control unit is developed under the ARIA environment ,which is provide by the robot manufacturer.
We are taking the voice data from the microphone using a soundcard.this data is stored
In an array.this earray is passed on to a function which extracts word from the array(i.e.
Spoken words are extracted & quiet periods are dumped).these words are sent to a function which extracts frequency as a function of time.this frequency vector of the spoken word.this vector is compared with reference vectors.one of the reference vectors would match(i.e. the inner product in this case greater than the other 5).the command correspondingto this reference vector is fed to the microcontroller.
In this project we are getting a user dependent isolated word recognition system with a recognition accuracy of about 85% using 6 words the accuracy can be improved further
And the system can be used for more number of word if during the trainingof the systemo
The noise conditions are improved
Applications:
We belive such a system would find wide variety of applications menu driven systems such as email readers household appliances like washing machines microwave ovens
And pagers and mobiles e.t.c will become voice controlled in future our project may find applications out their because inherently the number of possible inputs is limited using our soft ware these can be controlled through a network as well
20-02-2012, 04:13 PM
to get information about the topic navigation of mobile robot full report ppt and related topic refer the page link bellow
http://studentbank.in/report-behavior-ba...-ai-system
http://studentbank.in/report-robotics-projects
http://studentbank.in/report-mobile-robo...ing-system
http://studentbank.in/report-intelligent...using-rfid
http://studentbank.in/report-behavior-ba...-ai-system
http://studentbank.in/report-robotics-projects
http://studentbank.in/report-mobile-robo...ing-system
http://studentbank.in/report-intelligent...using-rfid
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