Paper
5 July 1995 Robot algorithm evaluation by simulating sensor faults
Richard Ree Brooks, S. Sitharama Iyengar
Author Affiliations +
Abstract
Recently developed algorithms in automation theory are often difficult to compare correctly since systems must interact with a changing environment. All algorithms are therefore dependent on sensor inputs which are notoriously subject to noise and errors. Proper comparison must be platform independent, but must also take sensor reliability problems into account. We have developed, and are using, a software simulator for comparative evaluation of robotics algorithms. The simulator uses an abstract sensor model which allows evaluation of the algorithms with various sensor reliability parameter values. By applying equivalent algorithms to a large number of randomly generated scenarios it is possible to make valid quantitative comparisons of average performance. This information is complementary to asymptotic time complexity measure which is the most common tool for algorithm comparison. Information is gathered which allows comparison according to criteria chosen by the user, such as distance traveled, number of sensor scans taken, or even collisions with obstacles in the environment. A preliminary discussion of a system capable of quantitative comparison of several algorithms for robot navigation in unknown terrains is presented. This system is in the final stages of acceptance testing, and promises to provide a testbed for future robot navigation research.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Richard Ree Brooks and S. Sitharama Iyengar "Robot algorithm evaluation by simulating sensor faults", Proc. SPIE 2484, Signal Processing, Sensor Fusion, and Target Recognition IV, (5 July 1995); https://doi.org/10.1117/12.213032
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Sensors

Evolutionary algorithms

Algorithm development

Computer simulations

Navigation systems

Environmental sensing

Robotics

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