In this paper, a heuristic method for simultaneous
rescue robot path-planning and mission scheduling is introduced
based on project management techniques, multi criteria decision
making and artificial potential fields path-planning. Groups of
injured people are trapped in a disastrous situation. These people are
categorized into several groups based on the severity of their
situation. A rescue robot, whose ultimate objective is reaching
injured groups and providing preliminary aid for them through a path
with minimum risk, has to perform certain tasks on its way towards
targets before the arrival of rescue team. A decision value is assigned
to each target based on the whole degree of satisfaction of the criteria
and duties of the robot toward the target and the importance of
rescuing each target based on their category and the number of
injured people. The resulted decision value defines the strength of the
attractive potential field of each target. Dangerous environmental
parameters are defined as obstacles whose risk determines the
strength of the repulsive potential field of each obstacle. Moreover,
negative and positive energies are assigned to the targets and
obstacles, which are variable with respects to the factors involved.
The simulation results show that the generated path for two cases
studies with certain differences in environmental conditions and
other risk factors differ considerably.
[1] J. Martinez, P. Ioannou, "Project scheduling using state-based
probibilistic decision networks," Simulation Conf. Proc. U.S.A. 1998,
pp. 1287-1294
[2] R. Soltani Zarrin, S. Khanmohammadi, "Scheduling rescue robot
mission", Proc. of International Conf. on Operations Research, Nov
2010, Italy, Year 6 Issu 71 (ISSN: 1307-6892), pp. 689-694,.
[3] M. Spong, S. Hutchinson, M.Vidyasagar, "Robot modeling and control",
John Wiley 2006.
[4] Xiaoyong Zhang and et al, "A rescue robot path planning based on Ant
Colony optimization algorithm", Information Technology and Computer
Science, 2009. ITCS 2009 International Conf., July 2009, p 180 - 183,
978-0-7695-3688-0
[5] Yan Hua Liang, Cheng Tao Cai,"Research on path planning of pine
pescue pobots pased on puzzy pontrol", Jornal of Applied Mechanics
and Materials, pp. 3593-3600, Dec 2010.
[6] Qin Shi-yin, GAO Shu-zheng, "Path planning for mobile rescue robots
in disaster areas with complex environments, Caii transaction on
intelligent systems,
[7] Y. Koren and J. Borenstein, "Potential field methods and their inherent
limitations for mobile robot navigation," Proc. IEEE Conf. Robotics and
Automation, Sacramento,1991, pp. 1398-1404.
[8] J. Latombe, Robot Motion Planning. Norwell, MA: Kluwer, 1991.
[9] S. S. Ge and Y. J. Cui, "New Potential Functions for Mobile Robot Path
Planning", IEEE transactions on robotics and automation, vol. 16, no. 5,
october 2000
[10] K. S. AlSultan and M. D. S. Aliyu, "A new potential field-based
algorithm for path planning," J. Intell. Robot. Syst., vol. 17, no. 3,
pp.265-282,Nov.1996
[1] J. Martinez, P. Ioannou, "Project scheduling using state-based
probibilistic decision networks," Simulation Conf. Proc. U.S.A. 1998,
pp. 1287-1294
[2] R. Soltani Zarrin, S. Khanmohammadi, "Scheduling rescue robot
mission", Proc. of International Conf. on Operations Research, Nov
2010, Italy, Year 6 Issu 71 (ISSN: 1307-6892), pp. 689-694,.
[3] M. Spong, S. Hutchinson, M.Vidyasagar, "Robot modeling and control",
John Wiley 2006.
[4] Xiaoyong Zhang and et al, "A rescue robot path planning based on Ant
Colony optimization algorithm", Information Technology and Computer
Science, 2009. ITCS 2009 International Conf., July 2009, p 180 - 183,
978-0-7695-3688-0
[5] Yan Hua Liang, Cheng Tao Cai,"Research on path planning of pine
pescue pobots pased on puzzy pontrol", Jornal of Applied Mechanics
and Materials, pp. 3593-3600, Dec 2010.
[6] Qin Shi-yin, GAO Shu-zheng, "Path planning for mobile rescue robots
in disaster areas with complex environments, Caii transaction on
intelligent systems,
[7] Y. Koren and J. Borenstein, "Potential field methods and their inherent
limitations for mobile robot navigation," Proc. IEEE Conf. Robotics and
Automation, Sacramento,1991, pp. 1398-1404.
[8] J. Latombe, Robot Motion Planning. Norwell, MA: Kluwer, 1991.
[9] S. S. Ge and Y. J. Cui, "New Potential Functions for Mobile Robot Path
Planning", IEEE transactions on robotics and automation, vol. 16, no. 5,
october 2000
[10] K. S. AlSultan and M. D. S. Aliyu, "A new potential field-based
algorithm for path planning," J. Intell. Robot. Syst., vol. 17, no. 3,
pp.265-282,Nov.1996
@article{"International Journal of Electrical, Electronic and Communication Sciences:53202", author = "Sohrab Khanmohammadi and Raana Soltani Zarrin", title = "Intelligent Path Planning for Rescue Robot", abstract = "In this paper, a heuristic method for simultaneous
rescue robot path-planning and mission scheduling is introduced
based on project management techniques, multi criteria decision
making and artificial potential fields path-planning. Groups of
injured people are trapped in a disastrous situation. These people are
categorized into several groups based on the severity of their
situation. A rescue robot, whose ultimate objective is reaching
injured groups and providing preliminary aid for them through a path
with minimum risk, has to perform certain tasks on its way towards
targets before the arrival of rescue team. A decision value is assigned
to each target based on the whole degree of satisfaction of the criteria
and duties of the robot toward the target and the importance of
rescuing each target based on their category and the number of
injured people. The resulted decision value defines the strength of the
attractive potential field of each target. Dangerous environmental
parameters are defined as obstacles whose risk determines the
strength of the repulsive potential field of each obstacle. Moreover,
negative and positive energies are assigned to the targets and
obstacles, which are variable with respects to the factors involved.
The simulation results show that the generated path for two cases
studies with certain differences in environmental conditions and
other risk factors differ considerably.", keywords = "Artificial potential field, GERT, path planning", volume = "5", number = "7", pages = "802-6", }