Anticipated trajectory based proportional navigation guidance scheme for intercepting high maneuvering targets

  • Amit Kumar
  • Aparajita Ojha
  • Prabin Kumar Padhy
Regular Papers Robot and Applications


Most of the existing target tracking schemes based on proportional navigation guidance laws require information on target’s acceleration to device their tracking strategies. Acceleration is computed or estimated continuously at each step to guide the interceptor. However, computation of acceleration is time consuming and often leads to inaccuracy, especially when the target is high maneuvering. Keeping this in view, a proportional navigation based guidance law for the interception of a high maneuvering target is presented that does not require estimation of the target’s acceleration to generate guidance command. The method is based on anticipating target’s trajectory using simple linear extrapolation and rotational correction. The interceptor predicts next position of the target and continuously adjusts its acceleration command to move towards the future position of the target. This simple modification not only helps in improving the time to intercept but also reduces number of target misses. Further, it is easier to implement for real time applications due to computational convenience. Performance of the method is compared with some of the most efficient navigation guidance laws with respect to the time taken in interception, distance traversed and the path followed by the interceptor. In addition, proof of convergence is provided. Simulation results are further verified through hardware implementation on wheeled mobile robots and results are quite encouraging.


Proportional navigation robot motion planning target tracking wheeled mobile robot 


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  1. [1]
    R. Isaacs, Differential Games: A Mathematical Theory with Applications to Warfare and Pursuit, Control and Optimization, Dover Publications, New York, 1965.zbMATHGoogle Scholar
  2. [2]
    L. Huang, “Velocity planning for a mobile robot to track a moving target -a potential field approach,” Robotics and Autonomous Systems, vol. 57, no. 1, pp. 55–63, 2009. [click]CrossRefGoogle Scholar
  3. [3]
    P. Shi and J. N. Hua, “Mobile robot dynamic path planning based on artificial potential field approach,” Advanced Materials Research, vol. 490-495, pp. 994–998, 2012. [click]CrossRefGoogle Scholar
  4. [4]
    X. Sun, W. Yeoh, and S. Koenig, “Moving target D* lite,” Proc. of the International Joint Conference on Autonomous Agents and Multiagent Systems, Toronto, Canada, pp. 67–74, 2010.Google Scholar
  5. [5]
    N. Basilico, N. Gatti, and F. Amigoni, “Patrolling security games: definition and algorithms for solving large instances with single patroller and single intruder,” Artificial Intelligence, vol. 184-185, pp. 78–123, 2012. [click]CrossRefzbMATHGoogle Scholar
  6. [6]
    T. Umeda, K. Sekiyama, and T. Fukuda, “Vision-based object tracking by multi-robots,” Journal of Robotics and Mechatronics, vol. 24, no. 3, pp. 531–539, 2012. [click]CrossRefGoogle Scholar
  7. [7]
    Y. Tian, Y. Li, and Z. Ren, “Vision-based adaptive guidance law for intercepting a manoeuvring target,” IET Control Theory and Applications, vol. 5, no. 3, pp. 421–428, 2011.MathSciNetCrossRefGoogle Scholar
  8. [8]
    J. P. Hwang, J. Baek, B. Choi, and E. Kim, “A novel partbased approach to mean-shift algorithm for visual tracking,” International Journal of Control, Automation and Systems, vol. 13, no. 2, pp. 443–453, 2015. [click]CrossRefGoogle Scholar
  9. [9]
    J. H. Lee, C. Lin, H. Lim, and J. M. Lee, “Sliding mode control for trajectory tracking of mobile robot in the RFID sensor space,” International Journal of Control, Automation and Systems, vol. 7, no. 3, pp. 429–435, 2009. [click]CrossRefGoogle Scholar
  10. [10]
    G. L. Li, H. Yan, and H. B. Ji, “A guidance law with finite time convergence considering autopilot dynamics and uncertainties,” International Journal of Control, Automation and Systems, vol. 12, no. 5, pp. 1011–1017, 2014. [click]CrossRefGoogle Scholar
  11. [11]
    T. Li, S. Chang, and W. Tong, “Fuzzy target tracking control of autonomous mobile by using infrared sensors,” IEEE Transactions on Fuzzy Systems, vol. 12, no. 4, pp. 491–501, 2004.CrossRefGoogle Scholar
  12. [12]
    M. A. Shirzi and M. R. H. Yazdi, “Active tracking using intelligent fuzzy controller and kernel-based algorithm,” Proc. of the IEEE International Conference on Fuzzy Systems, Taipei, Taiwan, pp. 1157–1163, 2011.Google Scholar
  13. [13]
    R. J. Wai and Y. W. Lin, “Adaptive moving-target tracking control of a vision-based mobile robot via a dynamic petri recurrent fuzzy neural network,” IEEE Transactions on Fuzzy Systems, vol. 21, no. 4, pp. 688–701, 2013.CrossRefGoogle Scholar
  14. [14]
    R. Paul, E. Aguirre, M. G. Silvente, and R. M. Salinas, “A new fuzzy based algorithm for solving stereo vagueness in detecting and tracking people,” International Journal of Approximate Reasoning, vol. 53, no. 4, pp. 693–708, 2012. [click]CrossRefGoogle Scholar
  15. [15]
    F. Kunwar, P. K. Sheridan, and B. Benhabib, “Predictive guidance-based navigation for mobile robots: a novel strategy for target interception on realistic terrains,” Journal of Intelligent & Robotic Systems, vol. 59, no. 3-4, pp. 367–398, 2010. [click]CrossRefzbMATHGoogle Scholar
  16. [16]
    F. Belkhouche, B. Belkhouche, and P. Rastgoufard, “Line of sight robot navigation toward a moving goal,” IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 36, no. 2, pp. 255–267, 2006.CrossRefGoogle Scholar
  17. [17]
    Z. Chunzhe and H. Yi, “ADRC based integrated guidance and control scheme for the interception of maneuvering targets with desired LOS angle,” Proc. of the 29th Chinese Control Conference, Beijing, China, pp. 6192–6196, 2010.Google Scholar
  18. [18]
    D. Ghose, “True proportional navigation with maneuvering target,” IEEE Transactions on Aerospace and Electronic Systems, vol. 30, no. 1, pp. 229–237, 1994.MathSciNetCrossRefGoogle Scholar
  19. [19]
    M. Mehrandezh, M. N. Sela, R. G. Fenton, and B. Benhabib, “Robotic interception of moving objects using ideal proportional navigation guidance technique,” Robotics and Autonomous Systems, vol. 28, no. 4, pp. 295–310, 1999. [click]CrossRefzbMATHGoogle Scholar
  20. [20]
    M. Mehrandezh, M. N. Sela, R. G. Fenton, and B. Benhabib, “Robotic interception of moving objects using an augmented ideal proportional navigation guidance technique,” IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, vol. 30, no. 3, pp. 238–250, 2000.CrossRefzbMATHGoogle Scholar
  21. [21]
    C. D. Yang and C. C. Yang, “Optimal pure proportional navigation for maneuvering targets,” IEEE Transactions on Aerospace and Electronic Systems, vol. 33, no. 3, pp. 949–957, 1997.CrossRefGoogle Scholar
  22. [22]
    G. Jiali and C. Wanchun, “Optimal proportional navigation guidance based on generalized predictive control,” Proc. of the 16th International Conference on System Theory, Control and Computing, Sinaia, Romania, pp. 1–6, 2012.Google Scholar
  23. [23]
    C. H. Wang and K. N. Hung, “Intelligent adaptive law for missile guidance using fuzzy neural networks,” International Journal of Fuzzy Systems, vol. 15, no. 2, pp. 182–191, 2013.Google Scholar
  24. [24]
    L. Liang and X. Wei, “Bearings-only maneuvering target tracking based on fuzzy clustering in a cluttered environment,” International Journal of Electronics and Communications, vol. 68, no. 2, pp. 130–137, 2014. [click]CrossRefGoogle Scholar
  25. [25]
    M. Keshmiri and M. Keshmiri, “Performance comparison of various navigation guidance methods in interception of a moving object by a serial manipulator considering its kinematic and dynamic limits,” Proc. of the 15th International Conference on Methods and Models in Automation and Robotics, Miedzyzdroje, Poland, pp. 212–217, 2010.Google Scholar
  26. [26]
    Y. Song, W. Chen, and X. Yin, “A new angular acceleration guidance law with estimation approach based on sliding mode observer against high maneuvering target,” Applied Mechanics and Materials, vol. 110-116, pp. 5249–5256, 2012. [click]CrossRefGoogle Scholar
  27. [27]
    A. Kumar and A. Ojha, “Performance evaluation of certain proportional navigation guidance schemes,” Proc. of the IEEE International Conference on Control, Automation, Robotics and Embedded systems, Jabalpur, India, pp. 1–7, 2013.Google Scholar
  28. [28]
    P. J. Yuan and J. S. Chem, “Ideal proportional navigation,” Journal of Guidance, Control and Dynamics, vol. 15, no. 5, pp. 1161–1165, 1992. [click]CrossRefGoogle Scholar
  29. [29]
    P. J. Nahin, Chases and Escapes: The Mathematics of Pursuit and Evasion, New Jersey, Princeton University Press, 2007.zbMATHGoogle Scholar
  30. [30]
    M. Mehrandezh, Navigation-Guidance-Based Robot Trajectory Planning for Interception of Moving Objects, Ph.D. Thesis, University of Toronto, 1999.Google Scholar

Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Amit Kumar
    • 1
  • Aparajita Ojha
    • 1
  • Prabin Kumar Padhy
    • 2
  1. 1.Computer Science and Engineering DisciplinePDPM Indian Institute of Information Technology Design and Manufacturing JabalpurJabalpurIndia
  2. 2.Electronics and Communication Engineering DisciplinePDPM Indian Institute of Information Technology Design and Manufacturing JabalpurJabalpurIndia

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