Technical University of Munich

@inproceedings{beetz_transparent_1998,
 author = {M Beetz and T Arbuckle and A Cremers and M 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)}},
 year = {1998},
 editor = {Prade, H.},
 pages = {632–636},
 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.},
}