Autonomous In-door Vehicles

  • Jun Feng Dong
  • Sean Efrem Sabastian
  • Tao Ming Lim
  • Yuan Ping Li
Reference work entry

Abstract

This chapter gives an overview to the state-of-art technology of autonomous mobile robots and focuses more specifically on autonomous indoor vehicles (AIVs) for the purpose of being more relevant to the manufacturing and industrial automation applications. Among the various locomotion designs, this chapter only introduces wheeled AIVs as wheeled platforms are predominant in the current commercially available AIVs. Four key research areas of wheeled AIVs, (1) design and modeling, (2) motion control, (3) sensing, (4) navigation, are reviewed in detail. The major AIV suppliers along with their key AIV products are then surveyed. The chapter ends with concluding remarks and a prediction of the trends of future AIV development.

Keywords

Transportation Ghost Sonar Extractor Willow 

References

  1. d’Andréa-Novel B, Campion G, Bastin G (1995) Control of nonholonomic wheeled mobile robots by state feedback linearization. Int J Robot Res 14:543–559CrossRefGoogle Scholar
  2. Asada HH, Wada M (1998) The superchair: a holonomic omnidirectional wheelchair with a variable footprint mechanism. Progress report, total home automation and health/elderly care consortium, 31 Mar 1998Google Scholar
  3. Aulinas J, Petillot Y, Salvi J, Lladó X (2008) The SLAM problem: a survey. In: International congress of the catalan association of artificial intelligence, Sant Martí d’Empúries (Spain) October 22–24, 2008Google Scholar
  4. Bezick SM, Pue AJ (2010) Inertial navigation for guided missile systems. J Hopkins Apl Tech Dig 28(4):331–342Google Scholar
  5. Borenstein J (1995) Internal correction of dead-reckoning errors with the compliant linkage vehicle. J Robot Syst 12(4):257–273CrossRefGoogle Scholar
  6. Borenstein J, Koren Y (1991) The vector field histogram-fast obstacle avoidance for mobilerobots. Robot Autom IEEE Trans 7(3):278–288CrossRefGoogle Scholar
  7. Brockett RW (1983) Asymptotic stability and feedback stabilization. In: Differential geometric control theory. Birkhäuser, Boston, pp 181–191Google Scholar
  8. Campion G, Bastin G, Dandrea B (1996) Structural properties and classification of kinematic and dynamic models of wheeled mobile robots. IEEE Trans Robot Autom 12(1):47CrossRefGoogle Scholar
  9. Canudas de Wit C, Khennouf H, Samson C, Sordalen O (1993) Nonlinear control design for mobile robots. Recent trends in mobile robotics. In: Zheng YF (ed) Word scientific series in robotics and automated systems, world scientific, vol 11, pp 121–156Google Scholar
  10. Cheng Y, Maimone MW (2006) Visual odometry on the mars exploration rovers. IEEE Robot Autom Mag: 54–62Google Scholar
  11. Courbon JJ, Mezouar Y, Guenard N, Martinet P (2010) Vision-based navigation of unmanned aerial vehicles. Control Eng Pract 18:789–799CrossRefGoogle Scholar
  12. De Luca A, Oriolo G, Samson C (1998) Feedback control of a nonholonomic carlike robot. In: Laumond JP (ed) Robot motion planning and control, vol 229, Lecture notes in control and information sciences. Springer, London, pp 171–253CrossRefGoogle Scholar
  13. De Luca A, Oriolo G, Vendittelli M (2001) Control of wheeled mobile robots: an experimental overview. Ramsete 270:181–226CrossRefGoogle Scholar
  14. Dellaert F, Fox D, Burgard W, Thrun S (1999) Monte carlo localization for mobile robots. In: Proceedings of the IEEE international conference on robotics and automation, vol 2, IEEE, Marriott Hotel, Renaissance Center, Detroit, MichiganGoogle Scholar
  15. Dijkstra EW (1959) A note on two problems in connexion with graphs. Numer Math 1:269–271CrossRefMATHMathSciNetGoogle Scholar
  16. Doucet A, de Freitas N, Murphy K, Russel S (2000) Rao-blackwellized particle filtering for dynamic Bayesian networks. In: Proceedings of the conference on uncertainty in artificial intelligence (UAI), Stanford, CA, USAGoogle Scholar
  17. Engelhard N, Endres F et al (2012) Real-time 3D visual SLAM with a hand-held RGB-D camera In: Proceedings of the ICRA, St. Paul, MN, USAGoogle Scholar
  18. Evennou F, Marx F (2006) Advanced integration of WiFi and inertial navigation systems for indoor mobile positioning. EURASIP J Appl Signal Process: 1–11Google Scholar
  19. Fojtu S, Havlena M (2012) Nao robot localization and navigation using fusion of odometry and visual sensor data. In: International conference on intelligent robotics and applications. Springer-Verlag, Berlin, pp 427–438Google Scholar
  20. Gong J, Duan Y, Man Y, Xiong G (2007) VPH+: an enhanced vector polar histogram method for mobile robot obstacle avoidance. In: Proceedings of the ICMA, Harbin, ChinaGoogle Scholar
  21. Grisetti G, Kummerle R et al (2010) Hierarchical optimization on manifolds for online 2D and 3D mapping. In: Proceedings of the ICRA, Anchorage, AlaskaGoogle Scholar
  22. Hahnel D, Burgard W, Fox D, Thrun S (2003) An efficient FastSLAM algorithm for generating maps of large-scale cyclic environment from raw laser range measurements. In: International conference on intelligent robots and systems, Las Vegas, USA, vol 1, pp 206–211Google Scholar
  23. Hart PE, Nilsson NJ, Raphael B (1968) A formal basis for the heuristic determination of minimum cost paths. IEEE Trans Syst Sci Cybern SSC4 4(2):100–107CrossRefGoogle Scholar
  24. Helmick DM, Cheng Y (2004) Path following using visual odometry for a mars rover in high slip environments. In: Proceedings 2004 I.E. Aerospace Conference, Big Sky, MT, pp 772–789Google Scholar
  25. Henry P, Krainin M et al (2010) RGB-D Mapping: using depth camera for dense 3D modeling of indoor environments. In: Proceedings of the ISER, Delhi, IndiaGoogle Scholar
  26. Hightower JA (2001) Design and Calibration of the SpotON Ad-Hoc Location Sensing System. UW CSE 00–02–02, University of Washington, Department of Computer Science and Engineering, Seattle, WAGoogle Scholar
  27. Jaulin L (2001) Path planning using intervals and graphs. Reliab Comput 7(1):1–15CrossRefMATHMathSciNetGoogle Scholar
  28. Javier Garcia V, Zeev Zalevsky H (2008) Patent no. US7433024B2. United States of AmericaGoogle Scholar
  29. Julier SJ, Uhlmann JK (1997) A new extension of the Kalman filter to nonlinear systems. In: Proceedings of AeroSense, Orlando, FloridaGoogle Scholar
  30. Konolige K, Agrawal M (2010) Large-scale visual odometry for rough terrain. In: 13th International symposium of robotics research, Hiroshima, Japan, pp 201–212Google Scholar
  31. Lavalle SM (2006) Planning algorithms. Cambridge University Press, New YorkGoogle Scholar
  32. Lee S (2009) Use of infrared light reflecting landmarks for localization. Industrial Robot: An International Journal 138–145Google Scholar
  33. Luo RH, Hong BR, Li MH (2004) Grid map building based on prediction of local features. J Harbin Inst Technol 36(7):877–879Google Scholar
  34. Mason, Mechanics of Manipulation (CMU), Spring 2013, lecture 5 slides available online: http://www.cs.cmu.edu/afs/cs/academic/class/16741-s07/www/lecture5.pdf
  35. Merlo S, Norgia M (2000) Fiber Gyroscope Principles. In Handbook of fibre optic sensing technology. University of Pavia/Wiley, Italy, John Wiley & Sons LtdGoogle Scholar
  36. Montemerlo M, Thrun S, Koller D, Wegbreit B (2003) FastSLAM 2.0: an improved particle filtering algorithm for simultaneous localization and mapping that provably converges. In: International joint conferences on artificial intelligence, Acapulco, MexicoGoogle Scholar
  37. Moustafa Youssef AA (2005) The Horus WLAN Location Determination System. 3rd international conference on Mobile systems, applications, and services (pp. 205–218). New York, NY, USA: Association for Computing MachineryGoogle Scholar
  38. Palacin J, Valgaon I (2006) The optical mouse for indoor mobile robot odometry measurement. Sensors Actuator 126:141–147CrossRefGoogle Scholar
  39. Park C, Chung H, Lee JG (2000) Point stabilization of mobile robots via state-space exact feedback linearization. Robot Comput Integ Manuf 16(5):353–363CrossRefGoogle Scholar
  40. Qingxiao Yu CY (2012) An autonomous restaurant service robot. Industrial Robot: An International Journal, 271–281Google Scholar
  41. Rencken W (1993) Concurrent localization and map building for mobile robots using ultrasonic sensors. In: Proceedings of the IEEE/RSJ international conference on intelligent robotics and systems, YokohamaGoogle Scholar
  42. Samson C (1993) Time-varying feedback stabilization of car-like wheeled mobile robots. Int J Robot Res 12(1):55–64CrossRefMathSciNetGoogle Scholar
  43. Samson C (1995) Control of chained systems. Application to path following and time-varying point-stabilization of mobile robots. IEEE Trans Automat Control 40(1):64–77CrossRefMATHMathSciNetGoogle Scholar
  44. Shenoy SJT (2005) Simultaneous localization and mobile robot navigation in a hybrid sensor network. Intelligent Robots and Systems (pp. 1636–41). IEEE, Edmonton, Alberta, CanadaGoogle Scholar
  45. Siegwart R, Nourbakhsh IR (2004) Introduction to autonomous mobile robots. MIT Press, Cambridge, MA. ISBN 0-262-19502-XGoogle Scholar
  46. Sung-Bu Kim JL (2007). Precise indoor localization system for a mobile robot using auto calibration algorithm. 13th International conference on advanced robotics. Jeju, South KoreaGoogle Scholar
  47. Tenmoku RK (2003) A wearable augmented reality system for navigation using positioning infrastructures and a pedometer. Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality, Washington, DC, USAGoogle Scholar
  48. Thrun S (2002) Robotic mapping: a survey. In: Exploring artificial intelligence in the new millenium. Morgan Kaufmann, San FranciscoGoogle Scholar
  49. Ulrich I, Borenstein J (1998) VFH+: reliable obstacle avoidance for fast mobile robots. Robotics and Automation, Leuven, BelgiumGoogle Scholar
  50. Yamano KA (2004) Self-localization of mobile robots with RFID system by using support vector machine. Intelligent Robotics and Systems (pp. 3756–3761), Sendai, Japan, IEEEGoogle Scholar

Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  • Jun Feng Dong
    • 1
  • Sean Efrem Sabastian
    • 1
  • Tao Ming Lim
    • 1
  • Yuan Ping Li
    • 1
  1. 1.Mechatronics GroupSingapore Institute of Manufacturing TechnologySingaporeSingapore

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