# A. A. Maciejewski

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- Publications
- Influence

Obstacle Avoidance for Kinematically Redundant Manipulators in Dynamically Varying Environments

- A. A. Maciejewski, C. Klein
- Mathematics
- 1 September 1985

The vast majority of work to date concerned with obstacle avoidance for manipulators has dealt with task descriptions in the form ofpick-and-place movements. The added flexibil ity in motion control… Expand

Task Matching and Scheduling in Heterogenous Computing Environments Using a Genetic-Algorithm-Based Approach

- L. Wang, H. Siegel, V. Roychowdhury, A. A. Maciejewski
- Computer Science
- J. Parallel Distributed Comput.
- 25 November 1997

To exploit a heterogeneous computing (HC) environment, an application task may be decomposed into subtasks that have data dependencies. Subtask matching and scheduling consists of assigning subtasks… Expand

The Singular Value Decomposition: Computation and Applications to Robotics

- A. A. Maciejewski, C. Klein
- Mathematics, Computer Science
- Int. J. Robotics Res.
- 1 December 1989

The singular value decomposition has been extensively used for the analysis of the kinematic and dynamic characteristics of robotic manipulators. Due to a reputation for being nu merically expensive… Expand

A local measure of fault tolerance for kinematically redundant manipulators

- R. Roberts, A. A. Maciejewski
- Mathematics, Computer Science
- IEEE Trans. Robotics Autom.
- 1 August 1996

When a manipulator suffers a joint failure, its performance can be significantly affected. If the failed joint is locked, the resulting manipulator Jacobian is given by the original Jacobian, except… Expand

Numerical filtering for the operation of robotic manipulators through kinematically singular configurations

- A. A. Maciejewski, C. Klein
- Mathematics, Computer Science
- J. Field Robotics
- 1 December 1988

The loss of independent degrees of freedom at singular configurations is an inherent characteristic of robotic manipulators. Due to the unavoidable singularity of mechanical wrists, singular… Expand

Dealing with the ill-conditioned equations of motion for articulated figures

- A. A. Maciejewski
- Computer Science
- IEEE Computer Graphics and Applications
- 1 May 1990

Realistic motion simulation for articulated figures has relied on the solution of linear systems of equations. Sometimes the solution of these equations presents a great deal of numerical difficulty,… Expand

Dynamically mapping tasks with priorities and multiple deadlines in a heterogeneous environment

- Jong-Kook Kim, Sameer Shivle, +7 authors R. Joshi
- Computer Science
- J. Parallel Distributed Comput.
- 1 February 2007

In a distributed heterogeneous computing system, the resources have different capabilities and tasks have different requirements. To maximize the performance of the system, it is essential to assign… Expand

A Study of Five Parallel Approaches to a Genetic Algorithm for the Traveling Salesman Problem

- L. Wang, A. A. Maciejewski, H. Siegel, V. Roychowdhury, Bryce D. Eldridge
- Computer Science
- Intell. Autom. Soft Comput.
- 2005

Abstract This paper presents a comparative study of five different coarse-grained parallel genetic algorithms (PGAs) using the traveling salesman problem as the case application. All of these PGAs… Expand

Fundamental Limitations on Designing Optimally Fault-Tolerant Redundant Manipulators

- R. Roberts, H. G. Yu, A. A. Maciejewski
- Mathematics, Computer Science
- IEEE Transactions on Robotics
- 1 October 2008

In this paper, the authors examine the problem of designing nominal manipulator Jacobians that are optimally fault tolerant to one or more joint failures. Optimality is defined here in terms of the… Expand

Fault tolerant properties of kinematically redundant manipulators

- A. A. Maciejewski
- Engineering, Computer Science
- Proceedings., IEEE International Conference on…
- 13 May 1990

A measure of fault tolerances for redundant manipulators is derived based on the remaining dexterity following the loss of degree of freedom. Using this measure as a criterion, a technique for… Expand