A S‐shaped feedrate based NURBS interpolator for synchronization of robot tool tip trajectory and attitude
Abstract Parametric interpolation is a popular choice for robot control, of the available methods, NURBS interpolation based on S‐shaped feed rate scheduling is an effective way to achieve smooth, continuous robot motion, making it a subject of significant research interest. However, there are three challenges associated with this approach. One issue that has been identified is that when a NURBS curve is split into multiple blocks, the resulting feed rate curve may become discontinuous if one or more blocks are too short. A further issue is that the NURBS curve cannot be fully executed due to errors in the calculation process. The final challenge is to ensure synchronous interpolation between the robot tip and the attitude. This paper proposes a high‐precision NURBS interpolator based on S‐shaped feedrate scheduling. The proposed design effectively addresses the issue of connection velocity between blocks. Furthermore, an optimization algorithm is proposed to ensure NURBS precision, to compensate for truncation error. In conclusion, a framework for synchronous interpolating the robot tooltip and attitude based on dual NURBS is proposed. The results of experiments demonstrate that our method effectively addresses the issue of NURBS curve blocks being too short. We observed a notable improvement in the curve execution rate, from 0.998752 to 0.999993.
Authors
- Lijin Fang (ORCID: https://orcid.org/0000-0002-2410-4870)
- Guanghui Liu
- Qiang Li (ORCID: https://orcid.org/0000-0002-4079-8999)
- Ming Zhang (ORCID: https://orcid.org/0000-0001-5202-5574)
- Fiona H. Tan (ORCID: https://orcid.org/0000-0002-5730-4895)
Institutions
- Shenyang University of Technology (CN)
- Shenzhen Technology University (CN)
- Northeastern University (CN)
Publication Details
- Journal
- Asian Journal of Control
- Published
- 2025-04-18
- DOI
- https://doi.org/10.1002/asjc.3685
- Citations
- 1
- Primary Topic
- Robotic Mechanisms and Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 1.21