Skip to main content Accessibility help
×
Home
Hostname: page-component-cf9d5c678-7bjf6 Total loading time: 0.23 Render date: 2021-08-01T01:16:09.353Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "metricsAbstractViews": false, "figures": true, "newCiteModal": false, "newCitedByModal": true, "newEcommerce": true, "newUsageEvents": true }

Article contents

A globally converging algorithm for adaptive manipulation and trajectory following for mobile robots with serial redundant arms

Published online by Cambridge University Press:  07 June 2013

Paul Moubarak
Affiliation:
Robotics and Mechatronics Laboratory, Department of Mechanical and Aerospace Engineering, The George Washington University, Washington, DC 20052, USA
Pinhas Ben-Tzvi
Affiliation:
Robotics and Mechatronics Laboratory, Department of Mechanical and Aerospace Engineering, The George Washington University, Washington, DC 20052, USA
Corresponding
E-mail address:

Summary

In this paper the tip-over stability of mobile robots during manipulation with redundant arms is investigated in real-time. A new fast-converging algorithm, called the Circles Of INitialization (COIN), is proposed to calculate globally optimal postures of redundant serial manipulators. The algorithm is capable of trajectory following, redundancy resolution, and tip-over prevention for mobile robots during eccentric manipulation tasks. The proposed algorithm employs a priori training data generated from an exhaustive resolution of the arm's redundancy along a single direction in the manipulator's workspace. This data is shown to provide educated initial guess that enables COIN to swiftly converge to the global optimum for any other task in the workspace. Simulations demonstrate the capabilities of COIN, and further highlight its convergence speed relative to existing global search algorithms.

Type
Articles
Information
Robotica , Volume 31 , Issue 8 , December 2013 , pp. 1299 - 1311
Copyright
Copyright © Cambridge University Press 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Abo-Shanab, R. F. and Sepehr, N., “On dynamic stability of manipulators mounted on mobile platforms,” Robotica 19 (4), 439449 (2001).CrossRefGoogle Scholar
2.Czarnetzki, S., Kerner, S. and Urbann, O., “Observer-based dynamic walking control for biped robots,” J. Robot. Auton. Syst. 57 (8), 839845 (2009).CrossRefGoogle Scholar
3.Huang, Q., Tanie, K. and Sugano, S., “Coordinated motion planning for a mobile manipulator considering stability and manipulation,” Int. J. Robot. Res. 19 (8), 732742 (2000).CrossRefGoogle Scholar
4.Kim, J., Chung, W. K., Youm, Y. and Lee, B. H., “Real-Time ZMP Compensation Method using Null Motion for Mobile Manipulators,” Proceedings of the IEEE International Conference on Robotics and Automation, Washington, DC (May 2005).Google Scholar
5.Korayem, M. H., Azimirad, V. and Nikoobin, A., “Maximum load-carrying capacity of autonomous mobile manipulator in an environment with obstacle considering tip over stability,” Int. J. Adv. Manuf. Technol. 46, 811829 (2010).CrossRefGoogle Scholar
6.Rey, D. A. and Papadoupoulos, E. G., “Online Automatic Tipover Prevention for Mobile Manipulators,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'97), France (Sep. 1997).Google Scholar
7.Meghdari, A., Naderi, D. and Alam, M. R., “Neural-network-based observer for real-time tipover estimation,” J. Mechatronics, 15, 9891004 (2005).CrossRefGoogle Scholar
8.Korayem, M. H., Ghariblu, H., Korayem, M. H., Ghariblu, H. and Basu, A., “Maximum allowable load on wheeled mobile manipulators imposing redundancy constraints,” J. Robot. Auton. Syst. 44 (2), 151159 (2004).CrossRefGoogle Scholar
9.Korayem, M. H., Nikoobin, A. and Azimirad, V., “Maximum load carrying capacity of mobile manipulators: Optimal control approach,” Robotica 27, 147159 (2009).CrossRefGoogle Scholar
10.Tang, Z. B., “Adaptive partitioned random search to global optimization,” IEEE Trans. Autom. Control 39 (11), 22352244 (1994).CrossRefGoogle Scholar
11.Grudi, G. Z. and Lawrence, P. D., “Iterative inverse kinematics with manipulator configuration control,” IEEE Trans. Robot. Autom. 9 (4), 476483 (1993).CrossRefGoogle Scholar
12.Sasaki, S., “On numerical techniques for kinematic problems of general serial-link robot manipulators,” Robotica 12 (4), 309322 (1994).CrossRefGoogle Scholar
13.Lenarcic, J., “Effective secondary task execution of redundant manipulators,” Robotica 16 (4), 457462 (1998).CrossRefGoogle Scholar
14.Zhang, Z. and Zhang, Y., “Variable joint-velocity limits of redundant robot manipulators handled by quadratic programming,” IEEE/ASME Trans. Mechatronics 18 (2), 674686 (2013).CrossRefGoogle Scholar
15.Kumar, P. P. and Behera, L., “Visual servoing of redundant manipulator with jacobian matrix estimation using self-organizing map,” J. Robot. Auton. Syst. 58 (8), 978990 (2010).CrossRefGoogle Scholar
16.Goldenberg, A. A. and Fenton, R. G., “A null-space solution of the inverse kinematics of redundant manipulators based on a decomposition of screws,” J. Mech. Design 115 (3), 530539 (1993).Google Scholar
17.Caccavale, F., Chiaverini, S. and Sicillano, B., “Second-order kinematic control of robot manipulators with Jacobian damped least-squares inverse: Theory and experiments,” IEEE/ASME Trans. Mechatronics 2 (3), 188194 (1997).CrossRefGoogle Scholar
18.Tchoń, K., “Repeatable, extended Jacobian inverse kinematics algorithm for mobile manipulators,” Syst. Control Lett. 55 (2), 8793 (2006).CrossRefGoogle Scholar
19.Zergeroglu, E., Dawson, D. D., Walker, I. W. and Setlur, P., “Nonlinear tracking control of kinematically redundant robot manipulators,” IEEE/ASME Trans. Mechatronics 9 (1), 129132 (2004).CrossRefGoogle Scholar
20.Sciavicco, L. and Siciliano, B., “A solution algorithm to the inverse kinematic problem for redundant manipulators,” IEEE Trans. Robot. Autom. 4 (4), 403410 (1988).CrossRefGoogle Scholar
21.Chung, W. J., Chung, W. K. and Youm, Y., “Kinematic control of planar redundant manipulators by extended motion distribution scheme,” Robotica 10 (3), 255262 (1992).CrossRefGoogle Scholar
22.Fahimi, F., Autonomous Robots, Modeling, Path Planning and Control (Springer, New York, 2008) ch. 2.Google Scholar
23.Chirikjian, G. S. and Burdick, J. W., “A modal approach to hyper-redundant manipulator kinematics,” IEEE Trans. Robot. Autom. 10 (3), 343354 (1994).CrossRefGoogle Scholar
24.Kumar, S., Premkumar, P., Dutta, A. and Behera, L., “Visual motor control of a 7-DOF redundant manipulator using redundancy preserving learning network,” Robotica 28 (6), 795810 (2010).CrossRefGoogle Scholar
25.Moubarak, P. and Ben-Tzvi, P., “Field Testing and Adaptive Manipulation of a Hybrid Mechanism Mobile Robot,” Proceedings of the IEEE International Symposium on Robotic and Sensor Environments (ROSE 2011), Montreal, Canada (Sep. 2011).Google Scholar
26.Ben-Tzvi, P., “Experimental validation and field performance metrics of a hybrid mobile robot mechanism,” J. Field Robot. 27 (3), 250267 (2010).Google Scholar
27.Ben-Tzvi, P., Goldenberg, A. A. and Zu, J. W., “Design and analysis of a hybrid mobile robot mechanism with compounded locomotion and manipulation capability,” J. Mech. Des. 130 (7), 113 (2008).CrossRefGoogle Scholar
28.Ben-Tzvi, P., Goldenberg, A. A. and Zu, J. W., “Articulated hybrid mobile robot mechanism with compounded mobility and manipulation and on-board wireless sensor/actuator control interfaces,” Mechatronics J. 20 (6), 627639 (2010).CrossRefGoogle Scholar
29.Carretero, J. A. and Nahon, M. A., “Solving minimum distance problems with convex or concave bodies using combinatorial global optimization algorithms,” IEEE Trans. Syst. Man Cybern. 35 (6), 11441155 (2005).CrossRefGoogle ScholarPubMed
30.Bryson, A. E. and Ho, Y. C., Applied Optimal Control: Optimization, Estimation, and Control, rev. ed. (Hemisphere, Washington, DC, 1975) ch. 1.Google Scholar
31.Zsolt, U., Lasdon, L., Plummer, J. C., Glover, F., Kelly, J. and Martí, R., “Scatter search and local NLP solvers: A multi-start framework for global optimization,” J. Comput. 19 (3), 328340 (2007).Google Scholar
32.Moubarak, P., Ben-Tzvi, P., “Spatial trajectory following with COIN algorithm,” available at: http://www.seas.gwu.edu/~bentzvi/COIN/COIN.html (2012) (accessed April, 2012).Google Scholar
33.Moubarak, P., Ben-Tzvi, P., “STORM Animation,” available at: http://www.seas.gwu.edu/~bentzvi/STORM/STORM_VR_Animation.html (Feb. 2011) (accessed April, 2012).Google Scholar
2
Cited by

Send article to Kindle

To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

A globally converging algorithm for adaptive manipulation and trajectory following for mobile robots with serial redundant arms
Available formats
×

Send article to Dropbox

To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

A globally converging algorithm for adaptive manipulation and trajectory following for mobile robots with serial redundant arms
Available formats
×

Send article to Google Drive

To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

A globally converging algorithm for adaptive manipulation and trajectory following for mobile robots with serial redundant arms
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *