• CN: 11-2187/TH
  • ISSN: 0577-6686

›› 2011, Vol. 47 ›› Issue (7): 8-15.

• Article • Previous Articles     Next Articles

Optimization Algorithm for Robotic Belt Surface Grinding Process

WANG Wei;YUN Chao;ZHANG Ling   

  1. Robotics Institute, Beihang University
  • Published:2011-04-05

Abstract: There are two prominent advantages for the robotic belt grinding system, flexible contact and machining with wide bandwidth. It is widely used to improve the surface quality and machining efficiency while finishing the works pieces with complex features. With complex contacts between the contact wheel and the work piece, the grinding paths for robot can be obtain by the theory of contact kinematics and the belt grinding technologies, but there lacks research on robotic grinding path planning. During the grinding process, it is the most important to conform the contact wheel to the local geometrical features on the contact area, so the curvature turns to be the most crucial factors to plan the grinding tool paths. For the local surfaces with small curvature, the arc length between the neighboring cutting locations becomes longer to ensure processing efficiency. Otherwise, for the local areas with large curvature, the arc length becomes shorter to decrease the chord error. A serial of planes are created to intersect with the target surface to be ground, and the corresponding intersecting lines are obtained. For each intersecting line, if the curvature at the cutter locations becomes larger than a quarter of the diameter of the contact wheel, a middle cutter location will be inserted to the tool path. The arc length between the neighboring cutting points is shortened under the constraint of the local curvature. The feasibility of this algorithm is completely approved by the off-line virtual simulation. The comparative belt grinding experiments between the algorithm and the classic tool path planning method, are designed, and the machining quality of the workpiece is increased by the algorithm.

Key words: Abrasive grinding, Arc length optimization, Curvature, Path planning, Robot

CLC Number: