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Towards Programming Tools for Robots That Integrate Probabilistic Computation and LearningBy Sebastian Thrun. Abstract: This paper describes a programming language extension of C++, called CES, specifically targeted towards mobile robot control. CES's design is motivated by a recent series of successful probabilistic methods for mobile robot control, with the goal of facilitating the development of such probabilistic software in future robot applications. CES extends C++ by two ideas: Computing with probability distributions, and built-in mechanisms for learning from examples as a new means of programming. An example program, used to control a mail-delivering robot with gesture commend interface, illustrates that CES may reduce the code development by two orders of magnitude. CES differs from other special-purpose programming languages in the field, which typically emphasize concurrency and real-time/event-driven processing. Available for download in
@INPROCEEDINGS{Thrun00b, AUTHOR = {Thrun, S.}, TITLE = {Towards Programming Tools for Robots That Integrate Probabilistic Computation and Learning}, YEAR = {2000}, BOOKTITLE = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)}, PUBLISHER = {IEEE}, ADDRESS = {San Francisco, CA} } |