@InProceedings{Bee98Tra,
  author    = {Michael Beetz and Tom Arbuckle and Armin Cremers and Markus Mann},
  title     = {Transparent, Flexible, and Resource-adaptive Image Processing for Autonomous Service Robots},
  booktitle = {Procs. of the 13th European Conference on Artificial Intelligence (ECAI-98)},
  editor    = {H. Prade},
  year      = {1998},
  pages     = {632--636},
  bib2html_pubtype  = {Refereed Conference Paper},
  bib2html_rescat   = {Plan-based Robot Control, Robot Vision},
  bib2html_groups   = {IAS},
  bib2html_funding  = {ignore},
  bib2html_keywords = {Robot, Planning, Vision},
  abstract = {We present the design of a programming system for IP routines which satisfies the requirements
              above. Our solution consists of RECIPE, a dynamically loadable, modular architecture in a
              distributed robot control system that provides the basic IP functionality and manages images
              and other IP data structures. It provides a variety of standard IP routines such as edge detectors,
              convolutions, noise reduction, segmentation, etc. RPLIP, an extension of the abstract machine
              provided by the robot control/plan language RPL. RPLIP provides suitable abstractions for images,
              regions of interest, etc, and supports a tight integration of the vision routines into the robot
              control system. Image Processing Plans that provide various methods for combining IP methods into
              IP pipelines. IP plans support the implementation of robust vision routines and the integration of
              other sensors such as laser range finders and sonars for object recognition tasks and scene
              analysis. Since vision routines are RPL programs, they can be constructed, revised, and reasoned
              about while the robot control program is being executed.}
}