Abstract
This paper presents the design and implementation of a real-time solution for the global control of robotic highway safety markers. Problems addressed in the system are: (1) poor scalability and predictability as the number of markers increases, (2) jerky movement of markers, and (3) misidentification of safety markers caused by objects in the environment.
An extensive analysis of the system and two solutions are offered: a basic solution and an enhanced solution. They are built respectively upon two task models: the periodic task model and the variable rate execution (VRE) task model. The former is characterized by four static parameters: phase, period, worst case execution time and relative deadline. The latter has similar parameters, but the parameter values are allowed to change at arbitrary times.
The use of real-time tasks and scheduling techniques solve the first two problems. The third problem is solved using a refined Hough transform algorithm and a horizon scanning window. The approach decreases the time complexity of traditional implementations of the Hough transform with only slightly increased storage requirements.
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Supported, in part, by grants from the National Science Foundation (CCR-0208619 and CNS-0409382) and the National Academy of Sciences Transportation Research Board-NCHRP IDEA Program (Project #90).
Jiazheng Shi received the B.E. and M.E. degrees in electrical engineering from Beijing University of Posts and Telecommunications in 1997 and 2000, respectively. In 2000, he worked with the Global Software Group, Motorola Inc. Currently, he is a Ph.D. candidate in the Computer Science and Engineering Department at the University of Nebraska–Lincoln. His research interests are automated human face recognition, image processing, computer vision, approximate theory, and linear system optimization.
Steve Goddard is a J.D. Edwards Associate Professor in the Department of Computer Science & Engineering at the University of Nebraska–Lincoln. He received the B.A. degree in computer science and mathematics from the University of Minnesota (1985). He received the M.S. and Ph.D. degrees in computer science from the University of North Carolina at Chapel Hill (1995, 1998).
His research interests are embedded, real-time and distributed systems with emphases in high assurance systems engineering and real-time, rate-based scheduling theory.
Anagh Lal received a B.S. degree in Computer Science from the University of Mumbai (Bombay), Mumbai, in 2001. He is currently a graduate research assistant at the University of Nebraska–Lincoln working on a M.S. in Computer Science, and a member of the ConSystLab. His research interests lie in Databases, Constraint Processing and Real Time Systems. Anagh will be graduating soon and is looking for positions at research institutions.
Jason Dumpert received a B.S. degree in electrical engineering from the University of Nebraska–Lincoln in 2001. He received a M.S. degree in electrical engineering from the University of Nebraska-Lincoln in 2004. He is currently a graduate research assistant at the University of Nebraska-Lincoln working on a Ph.D. in biomedical engineering. His research interests include mobile robotics and surgical robotics.
Shane M. Farritor is an Associate Professor in the University of Nebraska–Lincoln’s Department of Mechanical Engineering. His research interests include space robotics, surgical robotics, biomedical sensors, and robotics for highway safety. He holds courtesy appointments in both the Department of Surgery and the Department of Orthopaedic Surgery at the University of Nebraska Medical Center, Omaha. He serves of both the AIAA Space Robotics and Automation technical committee and ASME Dynamic Systems and Control Robotics Panel. He received M.S. and Ph.D. degrees from M.I.T.
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Shi, J., Goddard, S., Lal, A. et al. Global Control of Robotic Highway Safety Markers: A Real-time Solution. Real-Time Syst 29, 183–204 (2005). https://doi.org/10.1007/s11241-005-6884-y
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DOI: https://doi.org/10.1007/s11241-005-6884-y