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Bio-inspired behaviour-based control

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Abstract

The design and development of conventional controllers for robot platforms are sometimes too complex to achieve due to the fact that they require an exact model of the system and of the operating environment. The ability to pre-account for unknown operating environments is an important task for the controller to be robust. In contrast, biological controllers are model free and are based on simple working principles. Due to natural biological principles these controllers are adaptive and more robust than their conventional counterparts. In this paper, a behaviour-based controller has been developed, inspired by the concept of spinal fields found in frogs and rats. The performance of the controller has been verified on a Khepera robot platform.

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References

  • Anders KP (2000) Adaptive behaviour based robotics using on-board genetic programming. Candidate of Science Thesis, Norwegian University of Science and Technology

  • Arai Y, Fujii T, Asama H, Kataoka Y, Kaetsu H, Matsumoto A, Endo I (1997) Adaptive behaviour acquisition of collision avoidance among multiple autonomous mobile robots. In: Proceedings of IROS 97, pp 1762–1767

  • Arkin RC (1998) Behavior-based robotics. The MIT Press, Cambridge

    Google Scholar 

  • Bizzi E, Mussa-Ivaldi AF, Giszter S (1991) Computations underlying the execution of movement: a biological perspective. Science 253: 287–291

    Article  Google Scholar 

  • Brooks R (1986) A layered intelligent control systems for a mobile robot. IEEE J Robot Autom RA-2: 14–23

    MathSciNet  Google Scholar 

  • Guillot A, Meyer J-A (1994) Computer simulations of adaptive behaviour in animats. In: Proceedings of the IEEE conference on computer animation ’94, Geneva, 25–28 May, pp 22–131

  • Huelse M, Passermann F (2004) Expansion of neuro-modules by structure evolution. In: Gross H-M, Debes K, Boehme H-J (eds) Proceedings of 3rd workshop on self-organisation of adaptive behaviour. TU Ilmenau, Germany, pp 135–145

  • Jin T-S, Lee JM, Tso SK (2004) A new approach using sensor data fusion for mobile robot navigation. Robotica 22: 51–59

    Article  Google Scholar 

  • K-Team (2002) Khepera—user manual, version 1.1

  • Lau B, Triesch J (2004) Learning gaze following in space: a computational model. In: Proceedings of 3rd workshop on self-organisation of adaptive behaviour. TU Ilmenau, Germany, pp 241–250

  • Lorenz K (1973) Foundations of ethology. Springer-Verlag, New York

    Google Scholar 

  • Li W, Ma C, Wahl FM (1997) A neuron-fuzzy systems architecture for behaviour-based control of a mobile robot in unknown environments. Fuzzy Sets Syst 87: 133–140

    Article  Google Scholar 

  • Luo RC, Yih C-C, Su KL (2002) Multisensor fusion and integration: approaches, applications and future research directions. IEEE Sens J 2(2): 107–119

    Article  Google Scholar 

  • Mataric MJ (1995) Designing and understanding adaptive group behaviour. Adapt Behav 4(1): 50–81

    Article  Google Scholar 

  • Mataric MJ (2000) Getting humanoid to move and imitate. IEEE Intell Syst 15(4): 18–24

    Article  Google Scholar 

  • Payton DW (1986) An architecture for reflexive autonomous vehicle control. Proc IEEE Int Conf Robot Autom 3: 1838–1845

    Google Scholar 

  • Rusu P, Petriu EM, Whalen TE, Cornell A, Spoedler HJW (2003) Behaviour-based neuro-fuzzy controller for mobile robot navigation. IEEE Trans Instrum Measure 52(4): 1335–1340

    Article  Google Scholar 

  • Tinbergen N (1951) The study of instinct. Oxford University Press, New York

    Google Scholar 

  • Tikhonov AN, Arsenin VY (1977) Solutions to Ill-posed problems. Scripta series in mathematics. Translation edition, John F, Winston & Sons, Washington

  • Wasik Z, Saffiotti A (2002) A fuzzy behaviour-based control system for manipulation. In: Proceedings of 2002 IEEE/RSJ international conference on intelligent robots and systems. EPFL, Lausanne, pp 1596–16601

  • White FE (1991) Data fusion lexicon. Joint Directors of Laboratories, Technical Panel for C3. Data Fusion Sub-Panel Naval Oscean Systems Centre, San Diego

  • Yang G-Z, Hu X (2006) Multi-sensor fusion. In: Yang G-Z (eds) Body sensor networks, Chap. 8. Springer-Verlag, London

  • Zalama E, Gomez J, Paul M, Peran JR (2002) Adaptive behaviour navigation of a mobile robot. IEEE Trans Syst Man Cybernet—Part A: Syst Human 32(1): 160–169

    Article  Google Scholar 

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Correspondence to Nazmul H. Siddique.

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Siddique, N.H., Amavasai, B.P. Bio-inspired behaviour-based control. Artif Intell Rev 27, 131–147 (2007). https://doi.org/10.1007/s10462-008-9092-3

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