Abstract
In this paper, we generalize our random matrix based (RM-based) uncertainty model for manipulator Jacobian matrix to the dynamic model of the robotic systems. Conventional random variable based (RV-based) schemes require a detailed knowledge of the system parameters variation and may be not able to fully characterize the uncertainties of the complex dynamic systems. However, the proposed RM-based approach provides a probabilistic framework for systematic characterization of the uncertainties in the complex systems with limited available information. Moreover, RM-based uncertainty model is an efficient mathematical tool that ensures the kinematic and dynamic consistency and takes into account the system complexity, configuration, structural inter-dependencies, etc. The application of the RM-based uncertainty model is investigated using an example of kinematically redundant planar parallel manipulator (3-(P)RRR). The simulation results are compared with those obtained through conventional RV-based approach and the effectiveness of the proposed method is discussed.
Original language | English (US) |
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Article number | 6907447 |
Pages (from-to) | 4049-4054 |
Number of pages | 6 |
Journal | Proceedings - IEEE International Conference on Robotics and Automation |
DOIs | |
State | Published - Sep 22 2014 |
Event | 2014 IEEE International Conference on Robotics and Automation, ICRA 2014 - Hong Kong, China Duration: May 31 2014 → Jun 7 2014 |
ASJC Scopus subject areas
- Software
- Control and Systems Engineering
- Artificial Intelligence
- Electrical and Electronic Engineering