Plastic Grabber: Underwater Autonomous Vehicle Simulation for Plastic Objects Retrieval Using Genetic Programming

  • Gabrielė KasparavičiūtėEmail author
  • Stig Anton NielsenEmail author
  • Dhruv BoruahEmail author
  • Peter NordinEmail author
  • Alexandru DancuEmail author
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 339)


We propose a path planning solution using genetic programming for an autonomous underwater vehicle. Developed in ROS Simulator that is able to roam in an environment, identify a plastic object, such as bottles, grab it and retrieve it to the home base. This involves the use of a multi-objective fitness function as well as reinforcement learning, both required for the genetic programming to assess the model’s behaviour. The fitness function includes not only the objective of grabbing the object but also the efficient use of stored energy. Sensors used by the robot include a depth image camera, claw and range sensors that are all simulated in ROS.


Underwater autonomous vehicle Plastic collector Genetic programming 


  1. 1.
    Alvarez, A., Caiti, A., Onken, R.: Evolutionary path planning for autonomous underwater vehicles in a variable ocean. IEEE J. Oceanic Eng. 29(2), 418–429 (2004)CrossRefGoogle Scholar
  2. 2.
    Autonomous Marine Operations and Systems (AMOS) at NTNU: Blueye.
  3. 3.
    Boyan Slat: Ocean cleanup (2013).
  4. 4.
    Cauwenberghe, L.V., Janssen, C.R.: Microplastics in bivalves cultured for human consumption. Environ. Pollut. 193, 65–70 (2014). Scholar
  5. 5.
    Cheng, C.T., Fallahi, K., Leung, H., Chi, K.T.: A genetic algorithm-inspired uuv path planner based on dynamic programming. IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.) 42(6), 1128–1134 (2012)CrossRefGoogle Scholar
  6. 6.
    Ellen Macarthur Foundation: The new plastics economy rethinking the future of plastics (2013).
  7. 7.
    Eriksen, M., et al.: Plastic pollution in the world’s oceans: more than 5 trillion plastic pieces weighing over 250,000 tons afloat at sea. PLOS ONE 9(12), 1–15 (2014). Scholar
  8. 8.
    Floating Horizon: Marine litter.
  9. 9.
    Fogel, D.B., Fogel, L.J.: Optimal routing of multiple autonomous underwater vehicles through evolutionary programming. In: 1990 Proceedings of the Symposium on Autonomous Underwater Vehicle Technology, AUV 1990, pp. 44–47. IEEE (1990)Google Scholar
  10. 10.
    Fulton, M., Hong, J., Islam, M.J., Sattar, J.: Robotic detection of marine litter using deep visual detection models. arXiv preprint arXiv:1804.01079 (2018)
  11. 11.
    Lavender Law, K., van Sebille, E.: How much plastic is there in the ocean?
  12. 12.
    Nordin, P., Banzhaf, W.: Genetic programming controlling a miniature robot. In: Working Notes for the AAAI Symposium on Genetic Programming, AAAI 1995, vol. 61, p. 67. MIT, Cambridge (1995)Google Scholar
  13. 13.
    Nordin, P., Banzhaf, W.: An on-line method to evolve behavior and to control a miniature robot in real time with genetic programming. Adapt. Behav. 5(2), 107–140 (1997)CrossRefGoogle Scholar
  14. 14.
    Nordin, P., Banzhaf, W.: Real time control of a khepe. ra robot using genetic programmmg. Control Cybern. 26(3) (1997)Google Scholar
  15. 15.
    Ocean Conservancy: Report 2017 (2017).
  16. 16.
    Plastics Europe: Plastics - the facts 2013 : an analysis of European latest plastics production, demand and waste data (2013).
  17. 17.
    Prats, M., Pérez, J., Fernández, J.J., Sanz, P.J.: An open source tool for simulation and supervision of underwater intervention missions. In: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2577–2582. IEEE (2012)Google Scholar
  18. 18.
    Quigley, M., et al.: ROS: an open-source robot operating system. In: ICRA Workshop on Open Source Software, Kobe, Japan, vol. 3, p. 5 (2009)Google Scholar
  19. 19.
    Ranmarine: Aquadrone wasteshark.
  20. 20.
    Thompson, R.C.: Plastic debris in the marine environment: consequences and solutions. Mar. Nat. Conserv. Europe 193, 107–115 (2006)Google Scholar
  21. 21.
    Urban Rivers: Trash robot (2018).
  22. 22.
    Zeng, Z., Lian, L., Sammut, K., He, F., Tang, Y., Lammas, A.: A survey on path planning for persistent autonomy of autonomous underwater vehicles. Ocean Eng. 110, 303–313 (2015)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Chalmers University of TechnologyGothenburgSweden
  2. 2.IT University CopenhagenCopenhagenDenmark
  3. 3.thethamesproject.orgLondonUK
  4. 4.MIT Media LabCambridgeUSA

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