Michael Anschober
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Michael Anschober has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Andreas Nüchter
Julius-Maximilians-Universitt Wrzburg, Wrzburg, Germany
1 shared publication - Raimund Edlinger
Department of Smart Automation and Robotics, University of Applied Sciences Upper Austria Campus Wels, 4600 Wels, Austria
1 shared publication - Roman Froschauer
University of Applied Sciences Upper Austria
1 shared publication
Latest Publications
- Open Access
Inverse Kinematics of an Anthropomorphic 6R Robot Manipulator Based on a Simple Geometric Approach for Embedded Systems
This manuscript presents an efficient algorithm for solving the inverse kinematics problem of a 6R robot manipulator to be deployed on embedded control hardware. The proposed method utilizes the geometric relationship between the end-effector and the base of the manipulator, resulting in a computationally efficient solution. The approach aims to minimize computational complexity and memory consumption while maintaining the accuracy and real-time performance demonstrated by simulations and verified by experimental results on an embedded system. Furthermore, the manipulator is analyzed in terms of singularities, limits, the workspace, and general solvability. Due to the simplicity of the algorithm, a platform-independent implementation is possible. As a result, the average calculation time is reduced by a factor of five to eight and the average error is decreased by a factor of fifty compared to a powerful analytical solver.
Open AccessInverse Kinematics of an Anthropomorphic 6R Robot Manipulator Based on a Simple Geometric Approach for Embedded Systems
This manuscript presents an efficient algorithm for solving the inverse kinematics problem of a 6R robot manipulator to be deployed on embedded control hardware. The proposed method utilizes the geometric relationship between the end-effector and the base of the manipulator, resulting in a computationally efficient solution. The approach aims to minimize computational complexity and memory consumption while maintaining the accuracy and real-time performance demonstrated by simulations and verified by experimental results on an embedded system. Furthermore, the manipulator is analyzed in terms of singularities, limits, the workspace, and general solvability. Due to the simplicity of the algorithm, a platform-independent implementation is possible. As a result, the average calculation time is reduced by a factor of five to eight and the average error is decreased by a factor of fifty compared to a powerful analytical solver.