Feedrate scheduling of a five-axis hybrid robot for milling considering drive constraints

被引:13
|
作者
Li, Guangxi [1 ]
Liu, Haitao [1 ]
Yue, Wei [1 ]
Xiao, Juliang [1 ]
机构
[1] Tianjin Univ, Key Lab Modern Mech & Equipment Design, State Minist Educ, Tianjin 300350, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划; 欧盟地平线“2020”;
关键词
Feedrate scheduling; Five-axis machining; Parametric interpolation; Drive constraints; Hybrid robot; TOOL PATH; TRAJECTORY GENERATION; INTERPOLATION ALGORITHM; PARAMETRIC INTERPOLATOR; NURBS INTERPOLATOR; MACHINE-TOOLS; OPTIMIZATION; ACCELERATION; MANIPULATORS; CONSTANT;
D O I
10.1007/s00170-020-06559-1
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Characterized by high rigidity and precision, large working space, and reconfigurability, hybrid kinematic machines are widely used in the five-axis machining of large parts in situ. The feedrate is limited by the velocity, acceleration, and jerk of actuated joints in high-speed machining due to the nonlinear motion introduced by the use of revolute joints and parallel kinematic module. To achieve a good balance between the machining accuracy and efficiency, an offline feedrate-scheduling algorithm considering the drive constraints of a five-axis hybrid machine is proposed. By adding a dimension of the curve parameter, the feedrate profile expressed by a cubic uniform B-spline is mapped into a two-dimensional curve with the redefined control points. Then, the feedrate-scheduling process is completed by iteratively modulating the control points of feedrate profile. The velocity, acceleration, and jerk of actuated joints are calculated by the kinematic analysis for a dual non-uniform rational basis spline (NURBS) toolpath. Based on this, the feedrate constraint equations are derived considering the geometry and drive constraints. The scheduled feedrate profile remains constant in most parameter intervals, while it changes smoothly in transition intervals without violating constraints. Simulations and experiments are carried out on the TriMule600/800 machining platform, and the results validate the correctness and effectiveness of the proposed algorithm.
引用
收藏
页码:3117 / 3136
页数:20
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