Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.rcim.2020.101969
Title: Time-optimal tool motion planning with tool-tip kinematic constraints for robotic machining of sculptured surfaces
Authors: Lu, L
Zhang, J 
Fuh, JYH 
Han, J
Wang, H 
Issue Date: 1-Oct-2020
Publisher: Elsevier BV
Citation: Lu, L, Zhang, J, Fuh, JYH, Han, J, Wang, H (2020-10-01). Time-optimal tool motion planning with tool-tip kinematic constraints for robotic machining of sculptured surfaces. Robotics and Computer-Integrated Manufacturing 65 : 101969-101969. ScholarBank@NUS Repository. https://doi.org/10.1016/j.rcim.2020.101969
Abstract: © 2020 Elsevier Ltd A time-optimal motion planning method for robotic machining of sculptured surfaces is reported in this paper. Compared with the general time-optimal robot motion planning, a surface machining process provides extra constraints such as tool-tip kinematic limits and complexity of the curved tool path that also need to be taken into account. In the proposed method, joint space and tool-tip kinematic constraints are considered. As there are high requirements for tool path following accuracy, an efficient numerical integration method based on the Pontryagin maximum principle is adopted as the solver for the time-optimal tool motion planning problem in robotic machining. Nonetheless, coupled and multi-dimensional constraints make it difficult to solve the problem by numerical integration directly. Therefore, a new method is provided to simplify the constraints in this work. The algorithm is implemented on the ROS (robot operating system) platform. The geometry tool path is generated by the CAM software firstly. And then the whole machine moving process, i.e. the feedrate of machining process, is scheduled by the proposed method. As a case study, a sculptured surface is machined by the developed method with a 6-DOF robot driven by the ROS controller. The experimental results validate the developed algorithm and reveal its advantages over other conventional motion planning algorithms for robotic machining.
Source Title: Robotics and Computer-Integrated Manufacturing
URI: https://scholarbank.nus.edu.sg/handle/10635/168866
ISSN: 07365845
DOI: 10.1016/j.rcim.2020.101969
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