Abstract
This chapter describes dynamic models that are used for the identification of robot parameters. Considerations in this chapter apply to two types of robots: robots with gears (as an example see the description of the industrial robot IRp-6 [12]) and direct drive robots (DDA) without gears [9, 185]. These two classes of robots are the most common in industrial applications. We assume in this monograph that geometrical parameters of the robot are known; by geometrical parameters we mean parameters which are defined on the base of the modified Denavit—Hartenberg notation [10, 113]. Each link of a manipulator is characterised by dynamic parameters: mass, the centre of mass (which multiplied by mass represents a moment of the first order) and six parameters of the inertia tensor (which essentially are elements of a moment of the second order). The simplest way to measure these parameters is obviously to take the robot to pieces and then measure all the details thoroughly [1]. In most cases this is not possible, but when it is, it gives valuable benchmarks for other research. Therefore it is necessary to build a dynamic model for the robot itself. In practice these models are quite complicated and highly nonlinear with respect to joint positions, velocities, and accelerations. However, they are linear with respect to the dynamic parameters, which greatly simplifies the problem of identifying the dynamic parameters of the robot.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1998 Springer-Verlag London
About this chapter
Cite this chapter
Kozlowski, K. (1998). Robot dynamic models. In: Modelling and Identification in Robotics. Advances in Industrial Control. Springer, London. https://doi.org/10.1007/978-1-4471-0429-2_3
Download citation
DOI: https://doi.org/10.1007/978-1-4471-0429-2_3
Publisher Name: Springer, London
Print ISBN: 978-1-4471-1139-9
Online ISBN: 978-1-4471-0429-2
eBook Packages: Springer Book Archive