Affiliation:
1. Department of Mechanical Engineering McGill University Montreal, PQ Canada
Abstract
In this paper, we review and compare four algorithms for the identification of contact stiffness and damping during robot constrained motion. The intended application is dynamics modeling and simulation of robotic assembly operations in space. Accurate simulation of these tasks requires contact dynamics models, which in turn use contact stiffness and damping to calculate contact forces. Hence, our primary interest in identifying contact parameters stems from their use as inputs to simulation software with contact dynamics capability. Estimates of environmental stiffness and damping are also valuable for force tracking and stability of impedance controllers. The algorithms considered in this work include: a signal processing method, an indirect adaptive controller with modifications to identify environment damping, a model reference adaptive controller and a recursive least-squares estimation technique. The last three methods have been proposed for real-time implementation in impedance and force-tracking controllers. The signal processing scheme uses a frequency estimate calculated with fast Fourier transform of the force signal and is an off-line method. The algorithms are first evaluated using numerical simulation of a benchmark test. Experiments conducted with a robotic arm contacting a flexible wall provide a further demonstration of their performance. Our results indicate that the indirect adaptive controller has the best combination of performance and ease of use. In addition, the effect of persistently exciting signals is discussed.
Subject
Applied Mathematics,Artificial Intelligence,Electrical and Electronic Engineering,Mechanical Engineering,Modeling and Simulation,Software
Cited by
133 articles.
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