Performance Evaluation of Offline Motion Preparation Approaches on the Example of a Non-Linear Kinematics

In motion control, the generation of motion profiles for non-linear kinematics is usually computationally complex. In order to minimize the workload on the machine’s control system, the approach pursued is outsourcing complex calculation tasks to the offline area. In this offline motion preparation,...

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Bibliographic Details
Main Authors: Olaf Holowenko, Lucas Drowatzky, Steffen Ihlenfeldt
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/10/22/8014
Description
Summary:In motion control, the generation of motion profiles for non-linear kinematics is usually computationally complex. In order to minimize the workload on the machine’s control system, the approach pursued is outsourcing complex calculation tasks to the offline area. In this offline motion preparation, predefined criteria have to be taken into account to guarantee process stability on the real machine. During the motion preparation, a high performance is desired, characterized by less data generated and at the same time little computing effort. The evaluation will use the example of a motion specification, which is characterized by a large amount of data compared to conventional motion specifications. Thus, the demands on performance become even higher. This paper examines the performance of different motion preparation approaches known from literature. On the one hand, selected spline-based algorithms are discussed and compared. A recursive algorithm based on monomial splines is recommended for use in the example. On the other hand, a very simple approach based on the linearization of the non-linear workspace of the mechanism is presented and applied on the algorithms. With this, the performance increased significantly again.
ISSN:2076-3417