Deadline Missing Prediction for Mobile Robots through the Use of Historical Data
Mobile robotics is gaining an increasingly important
role in modern society. Several potentially dangerous or laborious
tasks for human are assigned to mobile robots, which are increasingly
capable. Many of these tasks need to be performed within a specified
period, i.e, meet a deadline. Missing the deadline can result in
financial and/or material losses. Mechanisms for predicting the
missing of deadlines are fundamental because corrective actions can
be taken to avoid or minimize the losses resulting from missing the
deadline. In this work we propose a simple but reliable deadline
missing prediction mechanism for mobile robots through the use of
historical data and we use the Pioneer 3-DX robot for experiments
and simulations, one of the most popular robots in academia.
[1] T. Tsubouchi and S. Arimoto, "Behavior of a mobile robot navigated
by an ldquo;iterated forecast and planning rdquo; scheme in the
presence of multiple moving obstacles,” in Robotics and Automation,
1994. Proceedings., 1994 IEEE International Conference on, 1994, pp.
2470–2475 vol.3.
[2] T. Tsubouchi, A. Hirose, and S. Arimoto, "A navigation scheme with
learning for a mobile robot among multiple moving obstacles,” in
Intelligent Robots and Systems ’93, IROS ’93. Proceedings of the 1993
IEEE/RSJ International Conference on, vol. 3, 1993, pp. 2234–2240
vol.3.
[3] J. Miura, H. Uozumi, and Y. Shirai, "Mobile robot motion planning
considering the motion uncertainty of moving obstacles,” in Proceedings.
1999 IEEE International Conference on Systems, Man, and Cybernetics,
1999, pp. 692–697.
[4] C. Shi, Y. Wang, and J. Yang, "A local obstacle avoidance method
for mobile robots in partially known environment,” Robot. Auton. Syst.,
vol. 58, no. 5, pp. 425–434, May 2010.
[5] Q. Zhu, J. Hu, and L. Henschen, "A new moving target interception
algorithm for mobile robots based on sub-goal forecasting and an
improved scout ant algorithm,” Applied Soft Computing, vol. 13, no. 1,
pp. 539 – 549, 2013.
[6] Y. Mei, Y.-H. Lu, Y. Hu, and C. S. G. Lee, "Energy-efficient motion
planning for mobile robots,” in Robotics and Automation, 2004.
Proceedings. ICRA ’04. 2004 IEEE International Conference on, vol. 5,
2004, pp. 4344–4349 Vol.5.
[7] M. Jia, G. Zhou, and Z. Chen, "An efficient strategy integrating grid and
topological information for robot exploration,” in Robotics, Automation
and Mechatronics, 2004 IEEE Conference on, vol. 2, 2004, pp. 667–672
vol.2.
[8] Y. Mei, Y.-H. Lu, C. S. G. Lee, and Y. Hu, "Energy-efficient
mobile robot exploration,” in Robotics and Automation, 2006. ICRA
2006. Proceedings 2006 IEEE International Conference on, 2006, pp.
505–511.
[9] Y. Mei, Y.-H. Lu, Y. Hu, and C. S. G. Lee, "A case study of mobile
robot’s energy consumption and conservation techniques,” in Advanced
Robotics, 2005. ICAR ’05. Proceedings., 12th International Conference
on, 2005, pp. 492–497.
[10] W. Zhang, Y.-H. Lu, and J. Hu, "Optimal solutions to a class of power
management problems in mobile robots,” Automatica, vol. 45, no. 4, pp.
989 – 996, 2009.
[11] A. Sadrpour, J. Jin, and A. Ulsoy, "Mission energy prediction for
unmanned ground vehicles,” in Robotics and Automation (ICRA), 2012
IEEE International Conference on, 2012, pp. 2229–2234.
[12] P. Plentz, "Mecanismos de previs˜ao de perda de deadline para sistemas
baseados em threads distribu´ıdas tempo real,” Doutorado, UFSC,
Florianop´olis - SC, 2008.
[13] S. Kirtane and J. Martin, "Application performance prediction in
autonomic systems,” in Proceedings of the 44th annual Southeast
regional conference, ser. ACM-SE 44. New York, NY, USA: ACM,
2006, pp. 566–572.
[14] E. Thereska, M. Abd-El-Malek, J. Wylie, D. Narayanan, and G. Ganger,
"Informed data distribution selection in a self-predicting storage
system,” in Autonomic Computing, 2006. ICAC ’06. IEEE International
Conference on, 2006, pp. 187–198.
[15] C. Tatibana, C. Montez, and R. Oliveira, "Soft real-time task
response time prediction in dynamic embedded systems,” in Software
Technologies for Embedded and Ubiquitous Systems, ser. Lecture Notes
in Computer Science, R. Obermaisser, Y. Nah, P. Puschner, and
F. Rammig, Eds. Springer Berlin Heidelberg, 2007, vol. 4761, pp.
273–282.
[16] W. Smith, I. Foster, and V. Taylor, "Predicting application run times
with historical information,” J. Parallel Distrib. Comput., vol. 64, no. 9,
pp. 1007–1016, Sept. 2004.
[17] L. Welch, A. Stoyenko, and T. Marlowe, "Response time prediction
for distributed processes specified in cart-spec,” Control Engineering
Practice, vol. 3, no. 5, pp. 651 – 664, 1995.
[18] E.-N. Huh and L. R. Welch, "Adaptive resource management for
dynamic distributed real-time applications,” J. Supercomput., vol. 38,
no. 2, pp. 127–142, Nov. 2006.
[1] T. Tsubouchi and S. Arimoto, "Behavior of a mobile robot navigated
by an ldquo;iterated forecast and planning rdquo; scheme in the
presence of multiple moving obstacles,” in Robotics and Automation,
1994. Proceedings., 1994 IEEE International Conference on, 1994, pp.
2470–2475 vol.3.
[2] T. Tsubouchi, A. Hirose, and S. Arimoto, "A navigation scheme with
learning for a mobile robot among multiple moving obstacles,” in
Intelligent Robots and Systems ’93, IROS ’93. Proceedings of the 1993
IEEE/RSJ International Conference on, vol. 3, 1993, pp. 2234–2240
vol.3.
[3] J. Miura, H. Uozumi, and Y. Shirai, "Mobile robot motion planning
considering the motion uncertainty of moving obstacles,” in Proceedings.
1999 IEEE International Conference on Systems, Man, and Cybernetics,
1999, pp. 692–697.
[4] C. Shi, Y. Wang, and J. Yang, "A local obstacle avoidance method
for mobile robots in partially known environment,” Robot. Auton. Syst.,
vol. 58, no. 5, pp. 425–434, May 2010.
[5] Q. Zhu, J. Hu, and L. Henschen, "A new moving target interception
algorithm for mobile robots based on sub-goal forecasting and an
improved scout ant algorithm,” Applied Soft Computing, vol. 13, no. 1,
pp. 539 – 549, 2013.
[6] Y. Mei, Y.-H. Lu, Y. Hu, and C. S. G. Lee, "Energy-efficient motion
planning for mobile robots,” in Robotics and Automation, 2004.
Proceedings. ICRA ’04. 2004 IEEE International Conference on, vol. 5,
2004, pp. 4344–4349 Vol.5.
[7] M. Jia, G. Zhou, and Z. Chen, "An efficient strategy integrating grid and
topological information for robot exploration,” in Robotics, Automation
and Mechatronics, 2004 IEEE Conference on, vol. 2, 2004, pp. 667–672
vol.2.
[8] Y. Mei, Y.-H. Lu, C. S. G. Lee, and Y. Hu, "Energy-efficient
mobile robot exploration,” in Robotics and Automation, 2006. ICRA
2006. Proceedings 2006 IEEE International Conference on, 2006, pp.
505–511.
[9] Y. Mei, Y.-H. Lu, Y. Hu, and C. S. G. Lee, "A case study of mobile
robot’s energy consumption and conservation techniques,” in Advanced
Robotics, 2005. ICAR ’05. Proceedings., 12th International Conference
on, 2005, pp. 492–497.
[10] W. Zhang, Y.-H. Lu, and J. Hu, "Optimal solutions to a class of power
management problems in mobile robots,” Automatica, vol. 45, no. 4, pp.
989 – 996, 2009.
[11] A. Sadrpour, J. Jin, and A. Ulsoy, "Mission energy prediction for
unmanned ground vehicles,” in Robotics and Automation (ICRA), 2012
IEEE International Conference on, 2012, pp. 2229–2234.
[12] P. Plentz, "Mecanismos de previs˜ao de perda de deadline para sistemas
baseados em threads distribu´ıdas tempo real,” Doutorado, UFSC,
Florianop´olis - SC, 2008.
[13] S. Kirtane and J. Martin, "Application performance prediction in
autonomic systems,” in Proceedings of the 44th annual Southeast
regional conference, ser. ACM-SE 44. New York, NY, USA: ACM,
2006, pp. 566–572.
[14] E. Thereska, M. Abd-El-Malek, J. Wylie, D. Narayanan, and G. Ganger,
"Informed data distribution selection in a self-predicting storage
system,” in Autonomic Computing, 2006. ICAC ’06. IEEE International
Conference on, 2006, pp. 187–198.
[15] C. Tatibana, C. Montez, and R. Oliveira, "Soft real-time task
response time prediction in dynamic embedded systems,” in Software
Technologies for Embedded and Ubiquitous Systems, ser. Lecture Notes
in Computer Science, R. Obermaisser, Y. Nah, P. Puschner, and
F. Rammig, Eds. Springer Berlin Heidelberg, 2007, vol. 4761, pp.
273–282.
[16] W. Smith, I. Foster, and V. Taylor, "Predicting application run times
with historical information,” J. Parallel Distrib. Comput., vol. 64, no. 9,
pp. 1007–1016, Sept. 2004.
[17] L. Welch, A. Stoyenko, and T. Marlowe, "Response time prediction
for distributed processes specified in cart-spec,” Control Engineering
Practice, vol. 3, no. 5, pp. 651 – 664, 1995.
[18] E.-N. Huh and L. R. Welch, "Adaptive resource management for
dynamic distributed real-time applications,” J. Supercomput., vol. 38,
no. 2, pp. 127–142, Nov. 2006.
@article{"International Journal of Information, Control and Computer Sciences:67085", author = "Edwaldo R. B. Monteiro and Patricia D. M. Plentz and Edson R. De Pieri", title = "Deadline Missing Prediction for Mobile Robots through the Use of Historical Data", abstract = "Mobile robotics is gaining an increasingly important
role in modern society. Several potentially dangerous or laborious
tasks for human are assigned to mobile robots, which are increasingly
capable. Many of these tasks need to be performed within a specified
period, i.e, meet a deadline. Missing the deadline can result in
financial and/or material losses. Mechanisms for predicting the
missing of deadlines are fundamental because corrective actions can
be taken to avoid or minimize the losses resulting from missing the
deadline. In this work we propose a simple but reliable deadline
missing prediction mechanism for mobile robots through the use of
historical data and we use the Pioneer 3-DX robot for experiments
and simulations, one of the most popular robots in academia.
", keywords = "Deadline missing, historical data, mobile robots, prediction mechanism.", volume = "8", number = "5", pages = "728-9", }
