Motion Recovery of Parallel Manipulators Using Task-Decomposition Approach

2012 ◽  
pp. 226-235
Author(s):  
Vahid Nazari ◽  
Leila Notash
Keyword(s):  
Parallel Manipulators ◽  
Decomposition Approach ◽  
Task Decomposition ◽  
Motion Recovery

scholarly journals Efficient multithreading for manycore processor: Multidimensional domain decomposition using Intel® TBB

2017 ◽  
Author(s):  
Etienne St-Onge ◽  
Benoit Scherrer ◽  
Simon Warfield
Keyword(s):  
Domain Decomposition ◽  
High Performance ◽  
Job Scheduling ◽  
Building Blocks ◽  
Massively Parallel ◽  
Decomposition Approach ◽  
Task Decomposition ◽  
Dynamic Task ◽  
Current Implementation ◽  
Generic Design

The Insight Toolkit (ITK) utilizes a generic design for image processing filters that allows many developers to rapidly implement new algorithms. While ITK filters benefit from a platform-independent and versatile multithreading capability, the current implementation does not easily achieve high performance. First, ITK relies on a static decomposition of the image into subsets of equal size which is highly inefficient when the computational complexity varies between subsets (unbalanced workloads). Second, the current domain decomposition is limited to subdivide the input domain along a single dimension (typically the slice dimension in a 3-D volume), which causes a multithreading under-utilization when the number of threads is larger than the size of this dimension when using massively parallel compute systems. We previously presented a new itk::TBBImageToImageFilter class that replaced the static task decomposition by a dynamic task decomposition for improved workload balancing, in which the job scheduling task was optimized using the Intel® Threading Building Blocks (TBB) library. In this work, we propose a new multidimensional dynamic image decomposition approach that allows decomposition over an arbitrary number of dimensions. This new generic multithreading capability, combined with the TBB dynamic task scheduler, substantially improves multithreading performance when using massively parallel processors.

MOTION RECOVERY AFTER JOINT FAILURE IN PARALLEL MANIPULATORS

2011 ◽  
Vol 35 (4) ◽  
pp. 559-571 ◽  
Author(s):  
Leila Notash
Keyword(s):  
Failure Modes ◽  
Jacobian Matrix ◽  
Null Space ◽  
Parallel Manipulators ◽  
Point Of View ◽  
Partial Recovery ◽  
Joint Failure ◽  
Motion Recovery ◽  
Motion Performance ◽  
Planar Parallel Manipulators

In this paper, the failure of parallel manipulators is investigated. Failure modes of parallel manipulators and their causes and effects from the kinematics point of view are discussed. Methodologies for investigating the effect of failures, due to joint failure or singularity, on the motion performance of manipulators are presented, and the criteria for full and partial recovery from these failures are established. The proposed methodologies are based on the projection of the lost motion onto the orthogonal complement of the null space of the Jacobian matrix after failure. The procedure is simulated for planar parallel manipulators to examine if after joint failure the required motion of manipulator could be fully recovered; as well as to calculate the corrections to the motion of remaining joints for recovering the lost motion.

Parametrical Synthesis of Linear Controllers in Aperiodical Systems on Basis of Decomposition Approach

2019 ◽  
Vol 12 (4) ◽  
pp. 192
Author(s):  
Sergey Anatolevich Gayvoronskiy ◽  
Tatiana Ezangina ◽  
Maxim Pushkarev ◽  
Ivan Khozhaev
Keyword(s):  
Decomposition Approach ◽  
Linear Controllers
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