Autonomous Multi-Target Interception in Dynamic Settings – On-Line Pursuer Task Allocation

1.Chung CF, Furukawa T. Coordinated pursuer control using particle filters for autonomous search-and-capture. Robot Auton Syst. 2009; 57:700-711.10.1016/j.robot.2008.11.002 Search in Google Scholar

2.Biswas S, Gupta S, Yu F, et al. Collaborative Multi-Target Tracking using Networked Micro-Robotic Vehicles. Def Transform Net-Centric Syst. 2007; 6578(12): 1-11.10.1117/12.717919 Search in Google Scholar

3.Sheridan PK, Kosicki P, Liu C, et al. On-Line Task Allocation for the Robotic Interception of Multiple Targets in Dynamic Settings. In: IEEE/ASME Conference on Advanced Intelligent Mechatronics; 2010 July 6-9; Montreal, Canada.10.1109/AIM.2010.5695786 Search in Google Scholar

4.Wu L, Xing C, Lu F, et al. An Anytime Algorithm Applied to Dynamic Weapon-Target Allocation Problem with Decreasing Weapons and Targets. In: IEEE Congress on Evolutionary Computation; 2008 June 1-6; Hong Kong. Search in Google Scholar

5.Beard BW, McLain TW, Goodrich MA, et al. Coordinated Target Assignment and Intercept for Unmanned Air Vehicles. IEEE Trans. Robot Autom. 2002; 18(6): 911- 922.10.1109/TRA.2002.805653 Search in Google Scholar

6.Tsalatsanis A, Yalcin A, Valavanis KP. Optimized Task Allocation in Cooperative Robot Teams. In: Mediterranean Conference on Control & Automation; 2009 June 2426; Thessaloniki, Greece.10.1109/MED.2009.5164551 Search in Google Scholar

7.Kunwar F, Benhabib B. Advanced Predictive Guidance Navigation for Mobile Robots: A Novel Strategy for Rendezvous in Dynamic Settings. Int. J Smart Sens Intell Syst. 2008; 1( 40): 858-890.10.21307/ijssis-2017-325 Search in Google Scholar

8.Agah F, Mehrandezh M, Fenton RG, et al. On-line Robotic Interception Planning Using Rendezvous-Guidance Technique. J. Intell Robot Syst.: Theory Appl. 2004; 40(1): 2344. Search in Google Scholar

9.Helvig CS, Robins G, Zelikovsky A. Moving-Target TSP and Related Problems. In: European Symposium on Algorithms; 1998 August 24-26; Venice Italy.10.1007/3-540-68530-8_38 Search in Google Scholar

10.Černý V. Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm. J Optim. Theory Appl. 1985; 45(1): 41-51.10.1007/BF00940812 Search in Google Scholar

11.Lin S, Kerninghan BW. An Effective Heuristic Algorithm for the Traveling-Salesman Problem. Oper Res. 1973; 21(2): 498-516.10.1287/opre.21.2.498 Search in Google Scholar

12.Derr K, Manic M: Multi-Robot, Multi-Target Particle Swarm Optimization Search in Noisy Wireless Environments. In: Conference on Human System Interaction. 2009, May 21-23; Catania, Italy.10.1109/HSI.2009.5090958 Search in Google Scholar

13.Chang KY, Jan GE, Su C-M, et al. Optimal Interceptions on Two-Dimensional Grids with Obstacles. J Navig. 2008; 61: 31-34.10.1017/S0373463307004262 Search in Google Scholar

14.McLain TW, Beard RW, Kelsey JM. Experimental Demonstration of Multiple Robot Cooperative Target Intercept. In: AIAA Guidance, Navigation, and Control Conference and Exhibit; 2002 August; Monterey, USA.10.2514/6.2002-4678 Search in Google Scholar

15.Flores Campos JA, Rosas Flores JA, Palacios Montufar C. Robot Trajectory Planning for Multiple 3D Moving Objects Interception: a Polynomial Interpolation Approach. In: Electronics, Robotics and Automotive Mechanics Conference; 2008 September 30 – October 4; Cuernavaca, Mexico.10.1109/CERMA.2008.87 Search in Google Scholar

16.Earl MG, D’Andrea R. A decomposition approach to multi-vehicle cooperative control. Robot Auton Syst. 2007; 55(4): 276-291.10.1016/j.robot.2006.11.002 Search in Google Scholar

17.Reimann J, Vachtsevanos G. UAVs in Urban Operations: Target Interception and Containment. J Intell Robot Syst. 2006; 47(4): 383–396.10.1007/s10846-006-9089-6 Search in Google Scholar

18.Mataric MJ, Sukhatme GS, Ostergaard EH. Multi-Robot Task Allocation in Uncertain Environments. Auton Robot. 2003; 14: 255-263.10.1023/A:1022291921717 Search in Google Scholar

19.Ostergard EH, Mataric MJ, Sukhatme GS. Distributed multi-robot task allocation for emergency handling. In: IEEE/RSJ International Conference on Intelligent Robots and Systems. 2001 October 29 – November 3; Hawaii USA. Search in Google Scholar

20.Ferrari S, Cai C, Fierro R, et al. A Geometric Optimization Approach to Detecting and Intercepting. In: American Control Conference. 2007 July 11-13; New York, USA.10.1109/ACC.2007.4282986 Search in Google Scholar

21.Borg JM, Mehrandezh M, Fenton RG, et al. Navigation-Guidance-Based Robotic Interception of Moving Objects in Industrial Settings. J Intell Robot Syst. 2002; 33(1): 1-23.10.1023/A:1014490704273 Search in Google Scholar

22.Mehrandezh M, Sela MN, Fenton RG, et al. Robotic Interception of Moving Objects Using an Augmented Ideal Proportional Navigation Guidance Technique. IEEE Trans on Syst Man Cybern. 2000; 30(3): 238-250.10.1109/3468.844351 Search in Google Scholar

23.Shetty VK, Sudit M, Nagi R. Priority-based assignment and routing of a fleet of unmanned combat aerial vehicles. Comput Oper Res. 2008; 25:1813-1828.10.1016/j.cor.2006.09.013 Search in Google Scholar

24.Zhu R, Sun D, Zhou Z. Cooperation Strategy of Unmanned Air Vehicles for Multitarget Interception. J Guid, Control, and Dyn. 2005; 28(5): 1068-1072.10.2514/1.14412 Search in Google Scholar

25.Kunwar F, Sheridan PK, Benhabib B. Predictive Guidance-Based Navigation for Mobile Robots: A Novel Strategy for Target Interception on Realistic Terrains. J Intell Robot Syst. 2010; 59(3-4): 367-398.10.1007/s10846-010-9401-3 Search in Google Scholar

26.Kirkpatrick S. Optimization by Simulated Annealing: Quantitative Studies. J Stat Phys. 1984; 34(5-6): 975-986.10.1007/BF01009452 Search in Google Scholar

27.Shneydor NA. Missile Guidance and Pursuit Kinematics, Dynamics, and Control. Horwood Publishing Limited: Great Britain; 1998. p.78-79.10.1533/9781782420590Search in Google Scholar