A Novel Mesh Following Technique Based on a Non-Approximant Surface Reconstruction for Industrial Robotic Path Generation

Abstract

Nowadays, industrial robot applications are required to customize the manufacturing of diverse products to reduce both downtime and standoff variability. The two methods for robot programming are regularly implemented to carry out that goal. The first one, online programming, requires a specialized operator to guide the robot through desired poses, and the quality of the result is directly limited by his skill level. On the other side, off-line programming uses software packaging to simulate robot applications before their implementation. It reduces downtime with respect to online programming but requires additional calibration steps. In this paper, a novel procedure is presented to obtain accurate surface approximations by combining linear interpolations generated during online programming with a triangulated surface reconstruction of a workpiece surface representation. The method uses a point cloud instead of a predefined mesh to reduce the standoff variability between the robotic tool center point and the surface. Additionally, a technique based on a penalized least squares method was implemented to smooth the trajectory, including position and orientation. The proposed methodology was validated with three well-known case studies involving real trajectories, with simulations in MATLAB and RobotStudio, as well as by experimentation with an industrial ABB robot. The quality of the results demonstrates a great efficiency of this method for path generation based on surface reconstruction. INDEX TERMS Robot programming procedure, industrial robot, path generation, surface reconstruction.

Novel surface optimization for trajectory reconstruction in industrial robot tasks

“…If a CAD model is not available, it is possible to take advantage of reverse engineering techniques using scanned data 15,16 offering discrete 3Dworkpiece models where special algorithms generate trajectories on point clouds and meshes. 8,13 In an earlier study, 3 the authors propose an incremental approach for automated trajectory generation from CAD model, the whole surface is meshed and divided into surface sections (SS) based on spray radius, and these SS are painted by spray gun located at a standoff distance from the surface section point (SSP) along the surface section normal (SSN). To calculate the SSP, the weighted average of all the centroids of the triangle inside the SS is used and the weighted average of the normals of the triangles in the SS determines the SSN.…”

“…On another side, the performance of off-line path planning methods is faster and often model-based 3D CAD. 7,[11][12][13] Some robotic applications take advantage of 3D-workpiece for diverse applications, for example, in Xingguo and Li, 14 a robotic model-based offline programming method made the projection of a 2D-plane onto the surface of a CAD model for machining processes, taking into consideration the spin angle of the tool. If a CAD model is not available, it is possible to take advantage of reverse engineering techniques using scanned data 15,16 offering discrete 3Dworkpiece models where special algorithms generate trajectories on point clouds and meshes.…”

Path Planning for Laser Cladding Robot on Artificial Joint Surface Based on Topology Reconstruction

“…The multi-joint industrial robot is gradually introduced in laser cladding because of the characteristics of high degree of freedom, flexibility and programmable [14,15]. Zheng et al [16] analyzed the geometric information of the part CAD (Computer Aided Design) model, and the cladding paths were automatically generated layer by layer according to the CAD model.…”

Smooth Trajectory Generation for Predefined Path With Pseudo Spectral Method

“…For example, to improve manufacturing quality with industrial manipulator, a penalized least squares method is employed to smooth the planned trajectory [1]. Considering contour error reduction, a NURBS interpolator with feedrate scheduling (NIFS) is presented, which consists of two parts: pre-processing and real-time interpolation [2].…”