Stereoscopic Vision for a Humanoid Robot Using Genetic Programming

  • Authors:
  • Christopher T. M. Graae;Peter Nordin;Mats G. Nordahl

  • Affiliations:
  • -;-;-

  • Venue:
  • Real-World Applications of Evolutionary Computing, EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoROB, and EvoFlight
  • Year:
  • 2000

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Abstract

In this paper we introduce a new approach to adaptive stereoscopic Vision. We use genetic programming, where the input to the individuals is raw pixel data from stereo image-pairs acquired by two CCD cameras. The output from the individuals is the disparity map, which is transformed to a 3D map of the captured scene using triangulation. The used genetic engine evolves machine-coded individuals, and can thereby reach high Performance on weak computer archiectures. The evolved individuals have an average disparity-error of 1.5 pixels which is equivalent to an uncertainty of about 10% of the true distance This work is motivated by applications to the control of autonomous humanoid robots -The Humanoid at Project Chalmers.