ORIGINAL_ARTICLE
Visual Tracking using Kernel Projected Measurement and Log-Polar Transformation
Visual Servoing is generally contained of control and feature tracking. Study of previous methods shows that no attempt has been made to optimize these two parts together. In kernel based visual servoing method, the main objective is to combine and optimize these two parts together and to make an entire control loop. This main target is accomplished by using Lyapanov theory. A Lyapanov candidate function is formed based on kernel definition such that the Lyapanov stability can be verified. The implementation is done in four degrees of freedom and Fourier transform is used for decomposition of the rotation and scale directions from 2D translation. In the present study, a new method in scale and rotation correction is presented. Log-Polar Transform is used instead of Fourier transform for these two degrees of freedom. Tracking in four degrees of freedom is synthesized to show the visual tracking of an unmarked object. Comparison between Log-Polar transform and Fourier transform shows the advantages of the presented method. KBVS based on Log-Polar transform proposed in this paper, because of its robustness, speed and featureless properties.
http://ijr.kntu.ac.ir/article_12494_943887b9de23947c5793a6d4f7f0ed1b.pdf
2015-06-01T11:23:20
2018-08-21T11:23:20
1
12
Visual Servoing
Lyapanov Function
Log
Polar Transform
Fourier Transform
Hamid
D. Taghirad
true
1
K.N. Toosi University of Technology
K.N. Toosi University of Technology
K.N. Toosi University of Technology
LEAD_AUTHOR
Hamid
D. Taghirad
taghirad@kntu.ac.ir
true
2
K.N. Toosi University of Technology
K.N. Toosi University of Technology
K.N. Toosi University of Technology
LEAD_AUTHOR
Fateme
Bakhshande
true
3
K.N. Toosi University of Technology
K.N. Toosi University of Technology
K.N. Toosi University of Technology
AUTHOR
A. Castano and S. Hutchinson, Visual compliance: Task directed visual servo control, IEEE Transactions on Robotics and Automation, 10 (1994) 334-342.
1
S. Hutchinson, G.D. Hager, P.I. Corke, A tutorial on visual servo control, 12 (1996) 651 -670.
2
W.J. Wilson, C.C. Williams Hulls, G.S. Bell, Relative end-effector control using cartesian position based visual servoing, IEEE Transactions on Robotics and Automation, 12 (1996) 684-696.
3
F. Chaumette and E. Malis, 2 1/2 D visual servoing: a possible solution to improve image-based and positionbased visual servoings, IEEE International Conference on Robotics and Automation, 1 (2000) 630-635.
4
F. Chaumette and S. Hutchinson, Visual servo control, part II: Advanced approaches, IEEE Robotics and Automation Magazine, 14 (2007) 109-118.
5
D. Kragic and H.I. Christensen, Technical report, Computational Vision and Active Perception Laboratory, (2002).
6
D. Comaniciu, V. Ramesh,. Meerc, IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(5) (2003) 564-575.
7
M. Dewan and G. Hager, Towards optimal kernel-based tracking, Computer Vision and Pattern Recognition, 1 (2006) 618-625.
8
Z. Fan, Y. Wu, M. Yang, Multiple collaborative kernel tracking. In Proc. IEEE Conf. on Computer Vision and Pattern Recognition , 2005.
9
G.D. Hager, M. Dewan, C.V. Stewart, Multiple kernel tracking with ssd, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1 (2004) 790-797.
10
J. Swensen, V. Kallem, N. Cowan, Empirical Characterization of Convergence Properties for Kernelbased Visual Servoing, Visual Servoing via Advanced Numerical Methods, Springer–Verlag, (2010) 23-38.
11
V. Kallem, J.P. Swensen, M. Dewan, G.D. Hager, N.J. Cowan, Kernel-Based Visual Servoing: Featureless Control using Spatial Sampling Functions.
12
V. Kallem, M. Dewan, J.P. Swensen, G.D Hager, N.J. Cowan, Kernel-based visual servoing, In IEEE/RSJ International . Conference. on Intelligent Robots and System, (2007) 1975-1980.
13
H. Araujo and J.M. Dias, "An introduction to the logpolar mapping", Second Workshop on Cybernetic Vision, pp. 139 - 144, 2002.
14
R. Matungka, "Studies on Log-Polar Transform for Image Registration and Improvements Using Adaptive Sampling and Logarithmic Spiral", 2009.
15
K. Palander and S.S. Brandt, "Epipolar geometry and log-polar transform in wide baseline stereo matching", International Conference on Pattern Recognition, pp. 1 -4, 2008.
16
R. Matungka, Y.F. Zheng and R.L.Ewing, "Image registration using adaptive polar transform", IEEE Transactions on Image Processing, 18, pp. 2340-2354, 2009.
17
R. Montoliu, V.J. Traver and F. Pla,"Log-polar mapping in generalized least-squares motion estimation", Proccedings of 2002 IASTED International Conference on Visualization, Imaging, and Image Processing (VIIP’2002), pp. 656-661, 2002.
18
H. Taghirad, M. Shahbazi, F. Atashzar and S. Rayatdoost, "Singular Free Motion Planning in Visual Servoing of Redundant Manipulators", Submitted to IET Computer Vision.
19
ORIGINAL_ARTICLE
Optimization of the Kinematic Sensitivity and the Greatest Continuous Circle in the Constant-orientation Workspace of Planar Parallel Mechanisms
This paper presents the results of a comprehensive study on the efficiency of planar parallel mechanisms, considering their kinetostatic performance and also, their workspace. This aim is approached upon proceeding single- and multi-objective optimization procedures. Kinetostatic performances of ten different planar parallel mechanisms are analyzed by resorting to a recent index, kinematic sensitivity. Moreover, the greatest possible continuous circle in the constant-orientation workspace of the latter mechanisms is considered as another objective for the optimization procedures. Seeking the set of design parameters which compromises simultaneous optimal values for the two aforementioned objectives, i.e., kinematic sensitivity and workspace, necessitates launching a multi-objective optimization process. The mathematical framework adopted for the optimization problem is based on genetic algorithm. The results of multi-objective optimization are based on the sets of Pareto points, offering the most reliable decisions to reconciliate between some conïicting objectives. To this end, the ten planar parallel mechanisms are sorted into two sets based on their type of actuator, some of them with prismatic actuators and the other ones with revolute actuators. Finally, a comparison between performances of these mechanisms, according to the obtained results, is carried out.
http://ijr.kntu.ac.ir/article_12492_2fe566d0d187b3709b959ecde7d7c738.pdf
2015-06-01T11:23:20
2018-08-21T11:23:20
12
21
Constant
orientation workspace
differential evolution
Kinematic sensitivity
NSGA
II
Planar parallel mechanisms
Mohammad
H. Saadatzi
msaadatz@mymail.mines.edu
true
1
Colorado School of Mines
Colorado School of Mines
Colorado School of Mines
AUTHOR
Mehdi
Tale Masouleh
m.t.masouleh@ut.ac.ir
true
2
University of Tehran
University of Tehran
University of Tehran
LEAD_AUTHOR
Morteza
Daneshmand
mortezad@ut.ee
true
3
University of Tartu
University of Tartu
University of Tartu
AUTHOR
J. Angeles, Fundamentals of Robotic Mechanical Systems: Theory, Methods, and Algorithms, Springer, (2006).
1
J., Angeles, Is there a Characteristic Length of a Rigidbody Displacement?, Mechanism and Machine Theory, Vol. 41(8), (2006), 884–896.
2
S. Bai, M. R. Hansen and T. O. Andersen, Modeling of a Special Class of Spherical Parallel Manipulators with Euler Parameters, Robotica, Vol. 27(2), (2009),161.
3
S. Bai, M. R. Hansen and J. Angeles, A Robust Forwarddisplacement Analysis of Spherical Parallel Robots Mechanism and Machine Theory, Vol. 44(12), (2009), 2204–2216.
4
N. Binaud, S. Caro and P. Wenger, Sensitivity Comparison of Planar Parallel Manipulators, Mechanism and Machine Theory, Vol. 45(11), (2010), 1477–1490.
5
I. A. Bonev, D. Chablat, P. Wenger, Working and Assembly Modes of the Agile Eye, IEEE International Conference on Robotics and Automation (ICRA), (2006), 2317–2322.
6
I. A. Bonev, Geometric Analysis of Parallel Mechanisms, Ph.D. Thesis, Laval University, Quebec, Canada, (2002).
7
I. A. Bonev, D. Zlatanov and C. Gosselin, Singularity Analysis of 3-DOF Planar Parallel Mechanisms via Screw Theory, Journal of Mechanical Design, Vol. 1 25(3), (2003), 573 – 581.
8
S. Briot and I. A. Bonev, Are Parallel Robots More Accurate than Serial Robots?, Transactions of the Canadian Society for Mechanical Engineering, Vol. 31(4), (2007), 445–456.
9
P. Cardou, S. Bouchard and C. Gosselin, Kinematicsensitivity Indices for Dimensionally Nonhomogeneous Jacobian Matrices, IEEE Transactions on Robotics, Vol. 26(1), (2010), 166–173.
10
S. Caro, F. Bennis, P. Wenger, et al., Tolerance Synthesis of Mechanisms: a Robust Design Approach, Journal of Mechanical Design, Vol. 127, (2005), 86–94.
11
M. Daneshmand, M. H. Saadatzi, M. Tale Masouleh, M. B. Menhaj, Optimization of Kinematic Sensitivity and Workspace of Planar Parallel Mechanisms, Multibody Dynamics Thematic Conference, Zagreb, Croatia, (2013), 391 -392.
12
M. Daneshmand, M. Tale Masouleh, M. H. Saadatzi, M. B. Menhaj, On the Optimum Design of Planar Parallel Mechanisms Based on Kinematic Sensitivity and Workspace, CCToMM Symposium, IFToMM, Montreal, Quebec, Canada, (2013).
13
B. Dasgupta and T. Mruthyunjaya, The Stewart Platform Manipulator: A Review, Mechanism and Machine Theory, Vol. 35(1), (2000), 15–40.
14
A. Engelbrecht, A., Computational Intelligence: An Introduction, Wiley, 2007.
15
E. Faghih, M. Daneshmand, M. H. Saadatzi, M. Tale Masouleh, A Benchmark Study on the Kinematic Sensitivity of Planar Parallel Mechanisms, CCToMM Symposium, IFToMM, Montreal, Quebec, Canada, (2013).
16
M. H. Farzaneh Kaloorazi, S. Esfahani, M. Tale Masouleh, M. Daneshmand, Dimensional Synthesis of Planar Cable-driven Parallel Robots via Interval Analysis, CCToMM Symposium, IFToMM, Montreal, Quebec, Canada, (2013).
17
C. Gosselin and J. Angeles, The Optimum Kinematic Design of a Spherical Three-degree-of-freedom Parallel Manipulator. Journal of Mechanisms, Transmissions, and Automation in Design, Vol. 111(2), (1989), 202–207.
18
C. M. Gosselin, J. F. Hamel, The Agile Eye: a Highperformance Three-degree-of-freedom Camera-orienting Device, IEEE International Conference on Robotics and Automation (ICRA), (1994), 781–786.
19
W. Khan and J. Angeles, The Kinetostatic Optimization of Robotic Manipulators: The Inverse and the Direct Problems, Journal of Mechanical Design, Vol. 128(1), (2006), 168–178.
20
X. Kong, C. Gosselin, Type Synthesis of Parallel Mechanisms, Springer, Heidelberg, 2007.
21
Y. Li, Q. Xu, Design and Analysis of a New 3-DOF Compliant Parallel Positioning Platform for Nanomanipulation, 5th IEEE Conference on Nanotechnology, (2005), 861 –864.
22
J. Merlet, Jacobian, Manipulability, Condition Number, and Accuracy of Parallel Robots, Journal of Mechanical Design, Vol. 128, (2006), 199–206.
23
K. Price, R. M. Storn, J. A. Lampinen, Differential Evolution: A Practical Approach to Global Optimization, first ed., Springer-Verlag, New York, 2005.
24
M. H. Saadatzi, M. Tale Masouleh, H. Taghirad, C. Gosselin, P. Cardou, On the Optimum Design of 3-RPR Parallel Mechanisms, 19th Iranian IEEE Conference on Electrical Engineering (ICEE), (2011), 1 –6.
25
M. H. Saadatzi, Workspace and Singularity Analysis of 5DOF Symmetrical Parallel Robots with Linear Actuators, Master’s Thesis, Faculty of Electrical and Computer Engineering, K.N. Toosi University of Technology, Tehran, Iran, (2011).
26
M. H. Saadatzi, M. Tale Masouleh, H. D. Taghirad, C. Gosselin and P. Cardou, Geometric Analysis of the Kinematic Sensitivity of Planar Parallel Mechanisms, Transactions of the Canadian Society for Mechanical Engineering, Vol. 35(4), (2011), 477–490.
27
M. H. Saadatzi, M. Tale Masouleh, H. D. Taghirad, C. Gosselin, M. Teshnehlab, Multi-Objective Scale Independent Optimization of 3-RPR Parallel Mechanisms, 13th World Congress in Mechanism and Machine Science, Guanajuato, Mexico, (2011).
28
L. J. Stocco, S. Salcudean and F. Sassani, On the Use of Scaling Matrices for Task-specific Robot Design, IEEE Transactions on Robotics and Automation, Vol. 15(5), (1999), 958–965.
29
R. Storn and K. Price, Differential Evolution - A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces, Journal of Global Optimization, Vol. 11 , (1997), 341 – 359.
30
Y. Takeda, H. Funabashi and Y. Sasaki, Development of a Spherical in-parallel Actuated Mechanism with Three Degrees of Freedom with Large Working Space and High Motion Transmissibility: Evaluation of Motion Transmissibility and Analysis of Working Space, JSME International Journal. Ser. C, Dynamics, Control, Robotics, Design and Manufacturing, Vol. 39(3), (1996), 541–548.
31
P. Wenger, C. Gosselin, B. Maill, B., A Comparative Study of Serial and Parallel Mechanism Topologies for Machine Tools, Parallel Kinematic Machine, (1999), 23- 32.
32
B. J. Yi, G. B. Chung, H. Y. Na, W. K. Kim and I. H. Suh, Design and Experiment of a 3-DOF Parallel Micromechanism Utilizing Flexure Hinges, IEEE Transactions on Robotics and Automation, Vol. 19(4), 604–612.
33
T, Yoshikawa, Manipulability of Robotic Mechanisms. The International Journal of Robotics Research, Vol. 4(2), (1985), 3–9.
34
ORIGINAL_ARTICLE
Identification of an Autonomous Underwater Vehicle Dynamic Using Extended Kalman Filter with ARMA Noise Model
In the procedure of designing an underwater vehicle or robot, its maneuverability and controllability must be simulated and tested, before the product is finalized for manufacturing. Since the hydrodynamic forces and moments highly affect the dynamic and maneuverability of the system, they must be estimated with a reasonable accuracy. In this study, hydrodynamic coefficients of an autonomous underwater vehicle (AUV) are identified using velocity and displacement measurements, and implementing an Extended Kalman Filter (EKF) estimator. The hydrodynamic coefficients are included in the augmented state vector of a six DOF nonlinear model. The accuracy and the speed of the convergence of the algorithm are improved by selecting a proper covariance matrix using the ARMA process model. This algorithm is used to estimate the hydrodynamic coefficients of two different sample AUVs: NPS AUV II and ISIMI. The comparison of the outputs of the identified models and the outputs of the real simulated models confirms the accuracy of the identification algorithm. This identification method can be used as an efficient tool for evaluating the hydrodynamic coefficients of underwater vehicles (robots), using the experimental data obtained from the test runs.
http://ijr.kntu.ac.ir/article_12493_91150588423e7ecdc30a7575494e61a4.pdf
2015-06-01T11:23:20
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22
28
Autonomous Underwater Vehicle
Hydrodynamic coefficients
Extended Kalman Filter
system identification
parameter estimation
Saeed
Ebrahimi
ebrahimi@yazd.ac.ir
true
1
Yazd University
Yazd University
Yazd University
AUTHOR
Mohammad
Bozorg
bozorg@yazd.ac.ir
true
2
Yazd University
Yazd University
Yazd University
LEAD_AUTHOR
Mehdi
Zare Ernani
mehdi.mze@gmail.com
true
3
Kavian Petrochemical Company
Kavian Petrochemical Company
Kavian Petrochemical Company
AUTHOR
P. Kodati, Xinyan, d. Experimental Studies on the Hydrodynamics of a Robotic Ostraciiform Tail Fin. IEEE Conference on Intelligent Robots and Systems, (2006), 5418 - 5423.
1
Bonato, V., Marques, E. and Constantinides, G. A., A Floating-point Extended Kalman Filter Implementation for Autonomous Mobile Robots, IEEE J. Signal Processing Systems, 56 (1 ), (2009), 41 -50.
2
Kim, J., Kim, K., Choi, H. S., Seong, W. and Lee, K. Y., Estimation of hydrodynamic coefficients for an AUV using nonlinear observers, IEEE J. Oceanic Eng., 27 (4), (2002), 830-840.
3
Healey, A. J., and Lienard, D., Multivariable sliding mode control for autonomous diving and steering of unmanned underwater vehicles, IEEE J. Oceanic Eng, 18, (1993), 327–339.
4
Yuh, J., Modeling and control of underwater robotic vehicles, IEEE Trans. Syst, Man, Cybern., 20, (1990), 1475–1483.
5
Pereira, J., and Duncan, A., System identification of underwater vehicles, Proceedings of the International Symposium on Underwater Technology, Tokyo, (2000), 419-424.
6
Ljung, L., System Identification: Theory for the User, Prentice-Hall, London, (1987).
7
Abkowitz, M.A., System identification techniques for ship maneuvering trial. Proceedings of Symposium on Control Theory and Navy Application, Monterey, USA, (1975), 337-393.
8
Feng, X. and Schulteis, J., Identification of high noise time series signals using hybrid ARMA modeling and neural network approach. IEEE Conference on Neural Networks, 3, (1993), 1780- 1785.
9
Bossley, K. M., Brown, M. and Harris, C. J., “Neurofuzzy identification of an autonomous underwater vehicle”, International Journal of Systems Science, 30 (9), (1999), 901 - 913.
10
Tiano, A., Sutton, R., Lozowicki, A., and Naeem, W., “Observer Kalman filter identification of an autonomous underwater vehicle”, Control Engineering Practice, 15, (2007), 727-739.
11
Fossen, T.I., Guidance and Control of Ocean Vehicles, John Wiley & Sons Ltd, (1994).
12
Saout, O., “Computation of hydrodynamic coefficients and determination of dynamic stability characteristic of an underwater vehicle including free surface effects”. MS Thesis, Florida Atlantic University, Dept. Mech. Eng., Boca Raton, Florida, (2003).
13
Mysorewala, M.F., Cheded, L. and Qureshi, A., "Comparison of nonlinear filters for the estimation of parameterized spatial field by robotic sampling". IEEE Conference on Industrial Electronics and Applications, Beijing, (2011 ), 2005-2010.
14
Simon, D., Optimal State Estimation: Kalman, Hinfinity, and Nonlinear Approaches, John Wiley & Sons Ltd., (2006).
15
Chui, C. K., and Chen, G., Kalman filtering with real time applications, Springer, New York, (1998).
16
Hyeon, K, Y., and Rhee, K. P., Identification of hydrodynamic coefficients in ship maneuvering equations of motion by Estimation-BeforeModeling technique, Ocean Engineering, 30, (2003), 2379-2404.
17
Jun, B. H., Park, J. Y., Lee, F. Y., “Development of the AUV ‘ISIMI’ and a free running test in an ocean engineering basin”, Oceanic Eng., 36, (2009), 2-14.
18
Best, M. C., Identifying tyre models directly from vehicle test data using an extended Kalman filter, Journal of Vehicle System Dynamics, 48, (2010), 171 -187.
19
Barbounis, T. G. and Theocharis, J. B., Recurrent neural networks for long-term wind speed and power prediction, Neuro computing, 69, (2006), 466-496.
20
Best, M. C., Gordon, T. J. and Dixon, P. J., An extended adaptive Kalman filter for real-time state estimation of vehicle handling dynamics, Journal of Vehicle System Dynamics, 34 (1 ), (2000), 57-75.
21
Roberts, G. N and Sutton, R., Advances in Unmanned Marine Vehicles, Institution of Engineering and Technology Publications, London, (2008).
22
Zare Ernani, M., Bozorg, M., and Ebrahimi, S., Identification of an AUV Dynamic Using Extended Kalman Filter, Proceeding of 18th Int. Conf. of Iranian Society of Mechanical Engineers, Tehran, Iran, (2010).
23
ORIGINAL_ARTICLE
Design and Kinematic Analysis of a 4-DOF Serial-Parallel Manipulator for a Driving Simulator
This paper presents the kinematic analysis and the development of a 4-degree-of-freedom serial-parallel mechanism for large commercial vehicle driving simulators. The degrees of freedom are selected according to the target maneuvers and the structure of human motion perception organs. Several kinematic properties of parallel part of the mechanism under study are investigated, including the inverse and the forward kinematics problems, workspace determination, singularity, and kinematic sensitivity analysis. The workspace of the parallel part of the mechanism is obtained by interval analysis. Moreover, using elimination theory, a univariate expression representing the forward kinematics solution of the parallel part is obtained.
http://ijr.kntu.ac.ir/article_12495_53d72b75fae2ad419b6fb69d2e8e59ed.pdf
2015-06-01T11:23:20
2018-08-21T11:23:20
29
37
driving simulator
Parallel mechanisms (PM)
Forward kinematics problem (FKP)
Kinematic sensitivity
Interval analysis
Mojtaba
Yazdani
true
1
K.N. Toosi University of Technology
K.N. Toosi University of Technology
K.N. Toosi University of Technology
AUTHOR
Mohammadreza
Arbabtafti
true
2
Shahid Rajaee Teacher Training University
Shahid Rajaee Teacher Training University
Shahid Rajaee Teacher Training University
AUTHOR
Mehdi
Tale-Masouleh
m.t.masouleh@ut.ac.ir
true
3
University of Tehran
University of Tehran
University of Tehran
AUTHOR
Milad
Hasanvand
true
4
K.N. Toosi University of Technology
K.N. Toosi University of Technology
K.N. Toosi University of Technology
AUTHOR
Ali
Nahvi
nahvi@kntu.ac.ir
true
5
K.N. Toosi University of Technology
K.N. Toosi University of Technology
K.N. Toosi University of Technology
LEAD_AUTHOR
Amir
Jaberi
a.jaberi@ut.ac.ir
true
6
K.N. Toosi University of Technology
K.N. Toosi University of Technology
K.N. Toosi University of Technology
AUTHOR
S. Advani, The Kinematic Design of Flight Simulator Motion-Bases, PhD Thesis, Delft University of Technology, (1998).
1
J. Slob, State of the Art Driving Simulators, a Literature Survey, Eindhoven University of Technology Department Mechanical Engineering Control Systems Technology Group, ( 2008).
2
J. Greenberg, R. Curry, M. Blommer, K. Kozak, B. Artz, L. Cathey and B. Kao, The Validity of LastSecond Braking and Steering Judgments in Advanced Driving Simulators DSC2006, Driving Simulator Conference, Paris, France, (2006).
3
A. Huesmann ,J. Nauderer, Applications to Driving Simulation and Their Requirements to the Tool, Motion Simulation Conference, Braunschweig, (2007).
4
C. Schwarz and T. Gates and Y. Papelis, Motion Characteristics of the National Advanced Driving Simulator, in Driving Simulator Conference, Michigan, US, (2003).
5
J. Challen, Reality Bytes, Driving Simulators, (2008) 50-53.
6
Lander Simulation and Training Solutions Tutor, Available: ttp://www.landersimulation.com, (2008).
7
Nasir Virtual Reality Driving Simulator, [Online]. Available: http://www.DrivingSimulator.ir.
8
F. Anooshahpour, A. Nahvi, N. Mehrabi, A. H. Haghighi, R. Kazemi, and S. Samiee, Design and Implementation of a Modified Classical Washout Filter Algorithm for ASARun Driving Simulator, ISME, (1 ) (2010)1 -7
9
I. A. Bonev, and J. Ryu, A Geometrical Method for Computing the Constant-Orientation Workspace of 6-PRRS Parallel Manipulators, Mechanism and Machine Theory, 36(1 ) (2001)1 -13.
10
M. Tale-Masouleh, M. H. Saadatzi, C. Gosselin, and H. D. Taghirad, A Geometric Constructive Approach for the Workspace Analysis of Symmetrical 5-PRUR Parallel Mechanisms (3T2R), Proceedings of the ASME, International Design Engineering Technical Conferences, (2010).
11
D. Chablat, and P. Wenger, Moveability and Collision Analysis for Fully-Parallel Manipulators, Proceedings of the Theory and Practice of Robots and Manipulators Symposium, RoManSy, (1998).
12
E. J. Haug, F. A. Adkins, and C. M. Luh, Operational Envelopes for Working Bodies of Mechanisms and Manipulators, Journal of Mechanical Design, 120(1 ) (1998)84-91.
13
J. P. Merlet, Parallel Robots, Springer, (2006).
14
J. P. Merlet, Solving the Forward Kinematics of a Gough-Type Parallel Manipulator with Interval Analysis, The International Journal of Robotics Research, 6(3) (2004)281 -290.
15
T. Yoshikawa, Analysis and Control of Robot Manipulators with Redundancy, Robotics Research: The First International Symposium, (1984)735-747.
16
J. K. Slisbury, and J. J. Craig, Articulated Hands, The International Journal of Robotics Research, 1 (1 ) (1982)4-17.
17
P. Cardou and S. Bouchard and C. Gosselin, Kinematic Sensitivity Indices for Dimensionally Nonhomogeneous Jacobian Matrices, IEEE Transactions on Robotics, 26(1) (2010) 166-173.
18
R. J. Telban, and F. M. Cardullo , Motion Cueing Algorithm Development:Human-Centered Linear and Nonlinear Approaches, The NASA STI Program Office, State University of New York, Binghamton, New York, (2005).
19
L. D. Reid, M.A. Nahon, Flight Simulation Motion Base Drive Algorithms, University of Toronto, UTIAS report, (1985).
20
M. Tale-Masouleh, C. Gosselin, M. Husty, and D. R. Walter, Forward Kinematic Problem of 5-RPUR Parallel Mechanisms (3T2R) with Identical Limb Structures, Mechanism and Machine Theory, (2011 ) 945-959.
21
M. Tale-Masouleh, C. Gosselin, M. H. Saadatzi, X. Kong, and H. D. Taghirad, Kinematic Analysis of 5- RPUR (3T2R) Parallel Mechanisms, Meccanica, 3(1 ) (2011)131 -146.
22
C. M. Gosselin, and J. P. Merlet, The Direct Kinematics of Planar Parallel Manipulators:Special Architectures and Number of Solutions, Mechanism and Machine Theory, 29(8) (1994)1083-1097.
23
J. P. Merlet, Direct Kinematics and Assembly Modes of Parallel Manipulators, The International Journal of Robotics Research, (1992).
24
R. E. Moore, R. B. Kearfott and M. J. Cloud, Introduction to Interval Analysis, The Society for Industrial and Applied Mathematics, (2009).
25
W. Kramer, I. Geulig, Interval Calculus in Maple: The Extension IntpakX to the Package Intpak of the Share-Library, University of Wuppertal, Germany, Available from http://www.math.uniwuppertal.de/wrswt/literatur.htm l, (2001).
26
Maple Application Center, [Online]. Available: http://www.mapleapps.com.
27
F. Hao, and J. P. Merlet, Multi-Criteria Optimal Design of Parallel Manipulators Based on Interval Analysis, Mechanism and Machine Theory, (2004)157-171.
28
C. M. Gosselin, J. Angeles, Singularity Analysis of Closed-loop Kinematic Chains, IEEE Transactions on robotics and automation, 6(3) (1990)281 -290.
29
S. A. Joshi, L. W. Tsai, Jacobian Analysis of Limited-DOF Parallel Manipulators, Transactions of the ASME, 124 (2002)254-258.
30
X. Kong, and C. Gosselin, Type Synthesis of Parallel of Mechanisms, Springer, (2007).
31
M. H. Saadatzi, M. Tale-Masouleh, H. D. Taghirad, C. Gosselin and P. Cardou, Geometric Analysis of the Kinematic Sensitivity of Planar Parallel Mechanisms, CCToMM Symposium, 26(1 ) (2011) 166-173.
32
ORIGINAL_ARTICLE
Control of Quadrotor Using Sliding Mode Disturbance Observer and Nonlinear Hâ
In this paper, a nonlinear model of the underactuated six degrees of freedom (6 DOF) quadrotor helicopter was derived based on the Newton-Euler formalism. A new nonlinear robust control strategy was proposed to solve the stabilizing and path following problems in presence of external disturbances and parametric uncertainties. The proposed control structure consist of a sliding mode control based on disturbance observer (SMDO) to track the reference trajectory together with a nonlinear Hâ controller to stabilize the rotational movements. Simulation results in the presence of aerodynamic disturbances and parametric uncertainties are presented to corroborate the effectiveness and the robustness of the proposed strategy.
http://ijr.kntu.ac.ir/article_12496_90601813885a23254cb41817db86767f.pdf
2015-06-01T11:23:20
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38
46
Disturbance Observer
Nonlinear H∞ Control
Sliding mode control
Quadrotor Helicopter
Kobra
Ghasemi
k.ghasemi@ec.iut.ac.ir
true
1
Isfahan University of Technology
Isfahan University of Technology
Isfahan University of Technology
AUTHOR
Ghasem
Alizadeh
alizadeh@tabrizu.ac.ir
true
2
University of Tabriz
University of Tabriz
University of Tabriz
LEAD_AUTHOR
P. Castillo, R. Lozano, A. Dzul, Modelling and control of mini-flying machines, SpringerVerlag, 2005.
1
A. Benallegue, A. Mokhtari , L. Fridman, Feedback Linearization and High Order Sliding Mode Observer For A Quadrotor UAV, Proceedings of the 2006 International Workshop on Variable Structure Systems, Italy , 2006
2
L. Besnard, Y. Shtessel, B. Landrum, Quadrotor vehicle control via sliding mode controller driven by sliding mode disturbance observer, Journal of the Franklin Institute (349), (2012), 658–684.
3
A. Mokhtari, A. Benallegue, B. Daachi, Robust feedback linearization and GH∞ controller for a quadrotor unmanned aerial vehicle, Journal of Electrical Engineering (57), (2006), 20–27 .
4
V. Guilherme, G Ortega. Manuel, R. Rubio. Francisco, Backstepping /Nonlinear H∞ Control for Path Tracking of a QuadRotor Unmanned Aerial Vehicle, American Control Conference, Washington, USA , 2008.
5
J. Pedersen, M. Petersen, Control of Nonlinear Plants Volume I., MS Thesis Mathematical Institute and Institute of Automation Technical University of Denmark, 1995
6
R. Olfati-Saber, Nonlinear control of underactuated mechanical systems with application to robotics and aerospace vehicles, Phd thesis, MIT, 2001.
7
A. Gessow, G.C. Myers, Aerodynamics of the Heilcopter, 3 nd Ed, College Park Press, College Park, MD, 1999.
8
P. Castillo, R. Lozano, A. E. Dzul. Modeling and Control of Mini-fiying Machines, SpringerVerlag, New York , 2005.
9
P. McKerrow, Modelling the Draganflyer four-rotor helicopter, Proceedings of the IEEE International Conference on Robotics and Automation, USA, 2004.
10
C. Edwards, S. Spurgeon, Sliding Mode Control: Theory And Applications, Taylor & Francis Ltd, 1998.
11
J. K. Carl, K. Seiichi, Disturbance Observer and Feedforward Design for a high speed DirectDrive Positioning Table, IEEE Transactions on control system technology 7 (5) (1999) 513-527.
12
A. Isidori, Nonlinear Control Systems, 3 nd Ed, Springer-Verlag, London, 1995.
13
A. Van der Schaft, , L2-gain analysis of nonlinear systems and nonlinear state feedback control, Transactions on Automatic Control 37 (6), (1992), 770-784.
14
A. Isidori, H∞ control via measurement feedback for affine nonlinear systems, International Journal of Robust and Nonlinear Control 4 (1994), 553-574.
15
W. Kang, P. K. De, A. Isidori, Flight control in a windshear via nonlinear H∞ methods, Proceedings of IEEE Control and Decision Conference (1992), 1 135-1142.
16
S. Bouabdallah, M. Becker, R. Siegwart, Autonomous Miniature Flying Robots: Coming Soon!, Robotics and Automation Magazine, (2006).
17
ORIGINAL_ARTICLE
Model Predictive Control and Stability Analysis of a Standing Biped with Toe-Joint
In this paper standing balance control of a biped with toe-joint is presented. The model consists of an inverted pendulum as the upper body and the foot contains toe-joint. The biped is actuated by two torques at ankle-joint and toe-joint to regulate the upper body in upright position. To model the interaction between foot and the ground, configuration constraints are defined and utilized. To stabilize the biped around upright position, model predictive control (MPC) is implemented by which the constraints can be incorporate to the optimal control algorithm properly. To assess stability of system and to find domain of attraction of the fixed point, concept of Lyapunov exponents is utilized. Using the proposed control and stability analysis, we studied the effect of toe-joint in improving the stability of the biped and in decreasing actuator demand, necessary for stabilizing the system. In addition, effect of toe-joint is studied in improving domain of attraction of the stabilized fixed pint.
http://ijr.kntu.ac.ir/article_12498_d23ca960080c146d85b660695b887d9e.pdf
2015-06-01T11:23:20
2018-08-21T11:23:20
47
54
Model Predictive Control
Toe
Joint
Standing balance control
Lyapunov exponents
Mohammad Jafar
Sadigh
true
1
Isfahan University of Technology
Isfahan University of Technology
Isfahan University of Technology
AUTHOR
Mohammad Jafar
Sadigh
jafars@cc.iut.ac.ir
true
2
Isfahan University of Technology
Isfahan University of Technology
Isfahan University of Technology
AUTHOR
Ehsan
Kouchakia
kouchaki@iauln.ac.ir
true
3
Islamic Azad University Lenjan branch
Islamic Azad University Lenjan branch
Islamic Azad University Lenjan branch
LEAD_AUTHOR
G. Colombo, M. Wirz and V. Dietz, Driven gait orthosis for improvement of locomotor training in paraplegic patient. Spinal Cord., Vol. 39, (2001), 252 – 255.
1
S. Jezernik, G. Colombo, T. Keller, H. Frueh and M. Morari, Robotic Orthosis Lokomat: A Rehabilitation and Research Tool. International Neuromodulation Society, Vol. 6(2), (2003), 108-115
2
J. F. Veneman, R. Kruidhof, E. E. G. Hekman, R. Ekkelenkamp, E. H. F. Van Asseldonk, and H. Van der Kooij, Design and Evaluation of the LOPES Exoskeleton Robot for Interactive Gait Rehabilitation. the 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, New York, Vol. 15(3), (2007), 379-386.
3
S. K. Banala, S. K. Agrawal and J. P. Scholz, Active Leg Exoskeleton (ALEX) for Gait Rehabilitation of MotorImpaired Patients. 2007 IEEE 10th International Conference on Rehabilitation Robotics, Noordwijk, The Netherlands, (2007), June 12-15, 401 -407.
4
D. J. Reinkensmeyer, D. Aoyagi, J. L. Emken, J. A. Galvez and W. Ichinose, Tools for understanding and optimizing robotic gait training. Journal of Rehabilitation Research & Development, August/September, Vol. 43(5), (2006), 657– 670 .
5
H. Vallery, M. Guidali, A. Duschau-Wicke and Robert Riener, Patient Cooperative Control: Providing Safe Support without Restricting Movement. IFMBE proceeding, (2009), 166-169.
6
H. Vallery, J. Veneman, Compliant Actuation of Rehabilitation Robots, IEEE Robotics & Automation Magazine,Vol. 15(3), (2008), 60-69.
7
J. F. Veneman, R. Ekkelenkamp, R. Kruidhof, F. C. T. Van der Helm and H. Van der Kooij, A Series Elastic- and Bowden-Cable-Based Actuation System for Use as Torque Actuator in Exoskeleton-Type Robots. The International Journal of Robotics Research Vol. 25(3), (2006), 261-281.
8
A. Duschau-Wicke, J. V. Zitzewitz, L. Lünenburger and R. Riener, Patient-Driven Cooperative Gait Training with the Rehabilitation Robot Lokomat. IFMBE Proceedings 22, (2008), 1616–1619.
9
M. Wellner, M. Guidali, J. Von Zitzewitz and Robert Riener, Using a Robotic Gait Orthosis as Haptic Display-A Perception-Based Optimization Approach, the IEEE 10th International Conference on Rehabilitation Robotics, (2007), 81 -88.
10
M. D. Hasankola, A. Dashkhaneh, M. M. Moghaddam, A. Mirzaie Saba, Design of a rotary elastic actuator for use as torque-actuator in rehabilitation robots, First RSI/ISM International Conference on Robotics and Mechatronics, (2013), 505-510.
11
Q. Wang, J. Qian, Y. Zhang, L. Shen, Zh. Zhang and Zh. Feng, Gait Trajectory Planning and Simulation for the Powered Gait Orthosis, the IEEE International Conference on Robotics and Biomimetics, Sanya, China, (2008), 1693- 1697.
12
A. Mirzaie Saba, Design, Simulation and Manufacturing of a Gait Rehabilitation Robot, MSc Thesis, Tarbiat Modares Univercity, (2012).
13
ORIGINAL_ARTICLE
Conceptual Design of a Gait Rehabilitation Robot
Gait rehabilitation using body weight support on a treadmill is a recommended rehabilitation technique for neurological injuries, such as spinal cord injury. In this paper, a new robotic orthosis is presented for treadmill training. In the presented design the criteria such as low inertia of robot components, backdrivability, high safety and degrees of freedom based on human walking are considered. This robot is composed of a leg exoskeleton for leg control and a segment for pelvis control. In the exoskeleton two degrees of freedom are considered for the hip joint and one for the knee joint. Also two degrees of freedom are considered for the pelvis joints. The inertia of moving components and the required force for the robot motion are measured to evaluate the robot backdrivability and transparency. Further, a walking algorithm is implemented on the robot and is tested on a human subject. Evaluation of the design showed that the robot is suitable for gait rehabilitation exercises.
http://ijr.kntu.ac.ir/article_12497_9637ea8724cc51fa6cd3242acc6f645b.pdf
2015-06-01T11:23:20
2018-08-21T11:23:20
55
61
Rehabilitation
Treadmill Training
Exoskeleton Backdrivability
Mohammad
D. Hasankola
true
1
Tarbiat Modares University
Tarbiat Modares University
Tarbiat Modares University
AUTHOR
Abbas
Ehsaniseresht
true
2
Hakim Sabzevari University
Hakim Sabzevari University
Hakim Sabzevari University
AUTHOR
Majid
M. Moghaddam
m.moghadam@modares.ac.ir
true
3
Tarbiat Modares University
Tarbiat Modares University
Tarbiat Modares University
LEAD_AUTHOR
Ali
Mirzaie Saba
true
4
Tarbiat Modares University
Tarbiat Modares University
Tarbiat Modares University
AUTHOR
F. Horak and L. Nashner, Central programming of postural movements: adaptation to altered supportsurface configurations, Journal of Neurophysiology, Vol. 55(6), (1986), 1369-1381
1
A.D. Kuo, An optimal control model for analyzing human postural balance, IEEE Transaction Biomedical Engineering, Vol. 42, (1986), 87-101.
2
C. Liu and C.G. Atkeson, Standing balance control using a trajectory library, IEEE/RSJ Int. Conf. on intelligent robots and systems, Louis, USA, (2009), 3031 -3036.
3
S. Ito, H. Takishita and M. Sasaki, A study of biped balance control using proportional feedback of ground reaction forces, SISE-ICASE. International Joint Conference, Bexco, Busan, Korea, (2006), 2368-2371.
4
B. Stephens, Integral Control of Humanoid Balance, The International Conference on Intelligent Robots and Systems (IROS’07), San Diego, CA, (2007).
5
A. Mahboobin, P. J. Loughlin, M. S. Redfern, S. O. Anderson, C. G. Atkeson, Sensory adaptation human balance control: Lessons for biomimetic robotic bipeds, School of computer science, Carnegie Mellon University, (2008).
6
M. Abdallah and A. Goswami, A biomechanically motivated two-phase strategy for biped upright balance control, IEEE Int. Conf. on robotics and automation, Barcelona, Spain, (2005), 2008-2013.
7
C. Yang and Q. Wu, On stabilization of bipedal robots during disturbed standing using the concept of Lyapunov exponents, Robotica, 24(5), (2006), 621 - 624.
8
C. Yang, Q. Wu and G. Joyce, Effects of constraints on bipedal balance control during standing, Int. J. Humanoid Robotics, 4, (2007), 753-775.
9
E. Kouchaki, Q. Wu and M. J. Sadigh, Effects of constraints on standing balance control of a bipeds with toe-joints, International Journal ofHumanoid Robotics, 9(3), (2012).
10
C. K. Ahn, M. C. Lee and S. J. Go, Development of a biped robot with toes to improve gait pattern, IEEE/ASME Int. Conference on Advanced Intelligent Mechatronics, (2003), 729-734.
11
R. Sellauoti and O. Stasse, Faster and Smoother Walking of humanoid HRP-2 with passive toe-joints, IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, Beijing, China, (2006), 4909-4914.
12
K. Yamamoto and T. Sugihara, Toe-joint mechanism using parallel four-bar linkage enabling humanlike multiple support at toe pad and toe tip, Int. Conf. on Humanoid Robots, Pittsburgh, USA, (2007), 410-415.
13
D. Tlalolini, C. Chevallereau, and Y. Aoustin, Human-like walking: optimal motion of a bipedal robot with toe-rotation motion, IEEE/ASME Transactions on Mechatronics, 16, (2011), 310-320.
14
E. Kouchaki, M.J. Sadigh, Effect of Toe-Joint Bending on Biped Gait Performance, IEEE Int. Conf. on robotics and biomimetics, Tianjin, China, (2010), 697-702.
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M. Cannon, Model predictive control, Lecture notes, Oxford University, (2011).
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18