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An evolutionary approach for the target search problem in uncertain environment

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Abstract

Search path planning is critical to achieve efficient information-gathering tasks in dynamic uncertain environments. Given task complexity, most proposed approaches rely on various strategies to reduce computational complexity, from deliberate simplifications or ad hoc constraint relaxation to fast approximate global search methods utilization often focusing on a single objective. However, problem-solving search techniques designed to compute near-optimal solutions largely remain computationally prohibitive and are not scalable. In this paper, a new information-theoretic evolutionary anytime path planning algorithm is proposed to solve a dynamic search path planning problem in which a fleet of homogeneous unmanned aerial vehicles explores a search area to hierarchically minimize target zone occupancy uncertainty, lateness, and travel/discovery time respectively. Conditioned by new observation outcomes and request events, the evolutionary algorithm episodically solves an augmented static open-loop search path planning model over a receding time horizon incorporating any anticipated information feedback. The proposed approach has shown to outperform alternate myopic and greedy heuristics, significantly improving relative information gain at the expense of modest additional travel cost.

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References

  • Agmon N, Hazon N, Kaminka GA (2008) The giving tree: constructing trees for efficient offline and online multi-robot coverage. Ann Math Artif Intell 52:143–168

    Article  MathSciNet  MATH  Google Scholar 

  • Ankenbrandt C (1991) An extension to the theory of convergence and a proof of the time complexity of genetic algorithms. In: Foundations of genetic algorithms. Morgan Kaufman, pp 53–68

  • Barkaoui M, Berger J, Boukhtouta A (2008) A hybrid genetic approach for the dynamic vehicle routing problem with time windows. Am J Math Manag Sci 28(1–2):131–154

    MathSciNet  MATH  Google Scholar 

  • Barkaoui M, Berger J, Boukhtouta A (2014) An information-theoretic-based evolutionary approach for the dynamic search path planning problem. In: International conference on advanced logistics and transport (ICALT), Hammamet, Tunisia

  • Barkaoui M, Berger J, Boukhtouta A (2015) Customer satisfaction in dynamic vehicle routing problem with time windows. J Appl Soft Comput 35:423–432

    Article  Google Scholar 

  • Bekhti M, Abdennebi M, Achir N, Boussetta K (2016) Path planning of unmanned aerial vehicles with terrestrial wireless network tracking. Wireless days, Toulouse

    Book  Google Scholar 

  • Berger J, Happe J, Gagne C, Lau M (2009) Co-evolutionary information gathering for a cooperative unmanned aerial vehicle team. In: 12th International conference on information fusion, FUSION ‘09

  • Berger J, Lo N, Barkaoui M (2016) Static target search path planning optimization with heterogeneous agents. Ann Oper Res 244(2):295–312

    Article  MathSciNet  MATH  Google Scholar 

  • Botzheim J, Toda Y, Kubota N (2012) Bacterial memetic algorithm for offline path planning of mobile robots. Memetic Computing 4(1):73–86

    Article  Google Scholar 

  • Bourgault F, Furukawa T, Durrant-Whyte HF (2003) Optimal search for a lost target in a bayesian world. In: Proceedings of the 4th international conference on field and service robotics (FSR’03), 24, Lake Yamanaka, Japan, pp 209–222

  • Bourgault F, Furukawa T, Durrant-Whyte HF (2003b) Coordinated decentralized search for a lost target in a Bayesian world. IEEE/RSJ Int Conf Intell Robots Syst 1:48–53

    Google Scholar 

  • Brooks A, Makarenko A, Williams S, Durrant-Whyte H (2006) Parametric POMDPs for planning in continuous state spaces. Robot Auton Syst 54(11):887–897

    Article  Google Scholar 

  • Chia SH, Su KL, Guo JH, Chung CY (2010) Ant colony system based mobile robot path planning. In: 4th International conference on genetic and evolutionary computing, Shenzhen, China

  • Cover T, Thomas J (2006) Elements of information-theory, 2nd edn. Wiley, Hoboken

    MATH  Google Scholar 

  • Dai R, Cochran JE (2009) Path planning for multiple unmanned aerial vehicles by parameterized cornu-spirals. In: Conference paper in proceedings of the American control conference, pp 2391–2396

  • Freundlich C, Mordohai P, Zavlanos MM (2015) Optimal path planning and resource allocation for active target localization. In: American control conference, Chicago, IL, USA, 2015, pp 3088–3093

  • Galceran Enric, Carreras Marc (2013) A survey on coverage path planning for robotics. Robot Auton Syst 61(12):1258–1276

    Article  Google Scholar 

  • Hrabar S (2008) 3D path planning and stereo-based obstacle avoidance for rotorcraft UAVs. In: IEEE/RSJ international conference on intelligent robots and systems, nice, France, 22–26 Sept 2008, pp 807–814

  • Lanillos P, Besada-Portas E, Pajares G, Ruz JJ (2012) Minimum time search for lost targets using cross entropy optimization. IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 602–609

  • Lanillos P, Zuluaga JY, Ruz J, Besada-Portas E (2013) A Bayesian approach for constrained multi-agent minimum time search in uncertain dynamic domains. In: Proceedings of the 15th annual conference on genetic and evolutionary computation. ACM, pp 391–398

  • Lanillos P, Gan SK, Besada-Portas E, Pajares G, Sukkarieh S (2014) Multi-UAV target search using decentralized gradient-based negotiation with expected observation. In: Information sciences, 282, 2014, pp 92–110

  • Larsen A, Madsen O, Solomon M (2002) Partially dynamic vehicle routing-models and algorithms. J Oper Res Soc 53:637–646

    Article  MATH  Google Scholar 

  • Lau H (2007) Optimal search in structured environments, PhD thesis, University of Technology, Sydney

  • Lau H, Dissanayake G (2005) Optimal search for multiple targets in a built environment. In: Proceedings of the IEEE/RSJ international conference intelligent robots and systems

  • Lin Y, Saripalli S (2014) Path planning using 3D dubins curve for unmanned aerial vehicles. In: Proceedings of the IEEE international conference on unmanned aircraft systems (ICUAS), Orlando, FL, USA, 27–30 May 2014, pp 296–304

  • Liu FH, Shen SY (1999) A route-neighborhood-based metaheuristic for vehicle routing problem with time windows. Eur J Oper Res 118:485–504

    Article  MATH  Google Scholar 

  • Lo N, Berger J, Noel M (2012) Toward optimizing static target search path planning. In: IEEE symposium on computational intelligence for security and defence applications, Ottawa, Canada, pp 1–7

  • Mac TT, Copot C, Tran DT, De Keyser R (2016) Heuristic approaches in robot path planning: a survey. Robot Auton Syst 86(12):13–28

    Article  Google Scholar 

  • Osman IH (1993) Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem. Ann Oper Res 41:421–451

    Article  MATH  Google Scholar 

  • Otte MW (2017) A survey of machine learning approaches to robotic path-planning. University of Colorado at Boulder, Report, August 2017, p 93. https://www.cs.colorado.edu/~mozer/Teaching/Computational%20Modeling%20Prelim/Otte.pdf

  • Peng Xingguang, Demin Xu (2012) Intelligent online path planning for UAVs in adversarial environments. Int J Adv Robot Syst 9:1–12

    Article  Google Scholar 

  • Perez-Carabaza S, Besada-Portas E, Lopez-Orozco JA, de la Cruz JM (2016) A real world multi-uav evolutionary planner for minimum time target detection. In: Proceedings of the genetic and evolutionary computation conference. ACM, pp 981–988

  • Pettersson PO, Doherty P (2006) Probabilistic roadmap based path planning for an autonomous unmanned helicopter. J Intell Fuzzy Syst 17:395–405

    Google Scholar 

  • Rekleitis I, New AP, Rankin ES, Choset H (2008) Efficient boustrophedon multi-robot coverage: an algorithmic approach. Ann Math Artif Intell 52:109–142

    Article  MathSciNet  MATH  Google Scholar 

  • Rylander B, Foster J (2001) Computational complexity and genetic algorithms. In: Proceedings of the world science and engineering society’s conference on soft computing, advances in fuzzy systems and evolutionary computation. World Science and Engineering Society Press, pp 248–253

  • Rylander B, Soule T, Foster J (2001) Computational complexity, genetic programming, and implications. In: Proceedings of the European genetic programming conference

  • Seuken S, Zilberstein S (2008) Formal models and algorithms for decentralized decision making under uncertainty. Auton Agent Multi-Agent Syst 17(2):190–250

    Article  Google Scholar 

  • Shaw P (1998) Using constraint programming and local search methods to solve vehicle routing problems. In: Maher M, Puget J-F (eds) Principles and practice of constraint programming. Lecture Notes in Computer Science. Springer, New York, pp 417–431

    Chapter  Google Scholar 

  • Solomon MM (1987) Algorithms for the vehicle routing and scheduling problems with time window constraints. Oper Res 35:254–265

    Article  MathSciNet  MATH  Google Scholar 

  • Stone LD (1975) Theory of optimal search. Academic Press, New York

    MATH  Google Scholar 

  • Sun Chuangchuang, Liu Yen-Chen, Dai Ran, Grymin David (2017) Two approaches for path planning of unmanned aerial vehicles with avoidance zones. J Guid Control Dyn 40(8):2076–2083

    Article  Google Scholar 

  • Svennebring J, Koenig S (2004) Building terrain-covering ant robots: a feasibility study. Auton Robots 16(3):313–332

    Article  Google Scholar 

  • Tisdale J, Zuwhan K, Hedrick JK (2009) Autonomous UAV path planning and Estimation: an online path planning framework for cooperative search and localization. IEEE Robot Autom Mag 16(2):35–42

    Article  Google Scholar 

  • Vidal R, Shakernia O, Kim HJ, Shim DH, Sastry S (2002) Probabilistic pursuit-evasion games: theory, implementation, and experimental evaluation. IEEE Trans Robot Autom 18(5):662–669

    Article  Google Scholar 

  • Washburn AR (1998) Branch and bound methods for a search problem. Nav Res Logist 45:243–257

    Article  MathSciNet  MATH  Google Scholar 

  • Wong S, MacDonald B (2003) A topological coverage algorithm for mobile robots. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems, Las Vegas, 2003, pp 1685–1690

  • Wood J, Hedrick K (2011) Multi-agent path planning for an unknown number of targets over dynamic space partitions. In: 50th IEEE conference on decision and control and european control conference, Orlando, FL, USA, 2011, pp 564–569

  • Yang S, Luo C (2004) A neural network approach to complete coverage path planning. IEEE Trans Syst Man Cybern B Cybern 34(1):718–724

    Article  Google Scholar 

  • Yang Y, Minai A, Polycarpou M (2005) Evidential map building approaches for multi-UAV cooperative search. In: Proceedings of the American control conference

  • Yu H, Meier K, Argyle M, Beard RW (2015) Cooperative path planning for target tracking in Urban environments using unmanned air and ground vehicles. IEEE/ASME Trans Mechatron 20(2):541–552

    Article  Google Scholar 

  • Yuan S, Lau H, Liu DK, Huang SD, Dissanayake G, Pagac D, Pratley T (2009) Simultaneous dynamic scheduling and collision-free path planning for multiple autonomous vehicles. In: International conference on information and automation, Macau, China, 2009

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Correspondence to M. Barkaoui.

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Barkaoui, M., Berger, J. & Boukhtouta, A. An evolutionary approach for the target search problem in uncertain environment. J Comb Optim 38, 808–835 (2019). https://doi.org/10.1007/s10878-019-00413-1

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