Parallel processing in industrial real-time applications
Parallel processing in industrial real-time applications
Parallel computation systems for robotics
Parallel computation systems for robotics
Scientific computing: an introduction with parallel computing
Scientific computing: an introduction with parallel computing
Fundamentals of Robotics: Analysis and Control
Fundamentals of Robotics: Analysis and Control
Modelling and Simulation of Robot Manipulators: A Parallel Processing Approach
Modelling and Simulation of Robot Manipulators: A Parallel Processing Approach
Efficient Scheduling Algorithms for Real-Time Multiprocessor Systems
IEEE Transactions on Parallel and Distributed Systems
Design and Evaluation of Effective Load Sharing in Distributed Real-Time Systems
IEEE Transactions on Parallel and Distributed Systems
Genetic Scheduling for Parallel Processor Systems: Comparative Studies and Performance Issues
IEEE Transactions on Parallel and Distributed Systems
A Framework for Reinforcement-Based Scheduling in Parallel Processor Systems
IEEE Transactions on Parallel and Distributed Systems
An Efficient Dynamic Scheduling Algorithm for Multiprocessor Real-Time Systems
IEEE Transactions on Parallel and Distributed Systems
Integrating job parallelism in real-time scheduling theory
Information Processing Letters
Evaluation of QoS-compliant overlays under denial of service attacks
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
Energy-efficient scheduling for parallel real-time tasks based on level-packing
Proceedings of the 2011 ACM Symposium on Applied Computing
Journal of Parallel and Distributed Computing
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Parallel architectures have not yet achieved the generality of sequential processing, especially in real-time applications. Real-time modeling and simulation of complex systems in areas such as robotics require thousands of computations in a fraction of a second, which can be prohibitive in terms of computer hardware. This often has resulted in an emphasis on tailor-made architectures, presenting a major obstacle in applications where the architecture must host a variety of algorithms.The author proposes using a parallel processing framework to solve the real-time robot simulation problem. Robot simulation facilities are essential for testing different robotics algorithms without the costs and hazards associated with experimental prototypes. The author also proposes using small-sized, coarse-grain networks of parallel processors to execute the algorithms. These networks consist of general-purpose T800 transputer chips.The author begins by explaining the motivation for this work and then carefully formulating the problem. He addresses architectural considerations and describes robot-arm-dynamics simulation. He then focuses on parallelism in robot simulation, describing the two computational modules: the computation of the dynamics and the solution of a linear system of equations.Finally, he presents the results of implementing the framework. These results reveal great potential, in terms of cost savings and performance, for using parallel processing in robotics computations.