Teaching-less robot system for finishing workpieces of various shapes using force control and computer vision

Kim

2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)

2012

Abstract²Deburring is a machining process which involves much noise, vibration and dust, so it can be harmful to workers. Therefore, much research has been done to use a manipulator to perform deburring instead of human workers. The precise tracking of the contour of an arbitrary-shaped part is of major concern in robotic deburring. In this study, a tool path generation method based on the CAD model and the direct teaching method is proposed to minimize the position and orientation errors of the workpieces. Without knowledge of the position and orientation of the workpiece, which is often hard to obtain, the optimal deburring trajectory can be generated by matching the extracted tool path from the CAD model to the teaching points. Furthermore, impedance control is used to avoid applying excessive contact force. From a series of experiments on robotic deburring, the performance of the proposed algorithm is verified.

Section: Introductionmentioning

confidence: 99%

Tool path generation based on matching between teaching points and CAD model for robotic deburring

Kim

2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)

2012

“…Robotic deburring requires high accuracy to track the edges of a workpiece with a consistent surface finish, which is impractical on a serial manipulator robot without a force control scheme [8]. Jinno et al [19] used computer vision path planning to design deburring and chamfering paths around planar workpieces using a monocular camera. The selected path was offset to the detected workpiece to account for the radius of the deburring tool with a known normal direction to apply force using a force controller.…”

Section: Background Of Thesismentioning

confidence: 99%

“…The selected path was offset to the detected workpiece to account for the radius of the deburring tool with a known normal direction to apply force using a force controller. The selection of the offset path and normal direction was not addressed in their study [19]. Section 3.2 of this thesis presents a literature review on computer vision path planning, but there was no solution found for selecting an offset path with force control in image-space.…”

Section: Background Of Thesismentioning

confidence: 99%

“…Computer vision path planning so far has been the most popular in robotic welding, in which the welding path is simply the position along a detected edge. Jinno et al [19] used image-space path planning to perform robotic deburring using a force control scheme. Force control requires a direction to apply force onto the workpiece, but the selection of the direction was not discussed in detail.…”

Section: Parameterize the Pathmentioning

confidence: 99%

See 1 more Smart Citation

Trajectory Planning for Contour Following and Robotic Deburring

Macmillan¹

The work of this thesis is part of the RoboDeb project, aimed at investigating the application of industrial robots on deburring sheet metal parts. This thesis presents investigations, developments, and implementations of trajectory planning algorithms to automate trajectory design. This thesis first develops custom CAD/CAM software called the Planar Computer Automated Trajectory (PCAT) planning algorithm to establish baseline performance. Trajectory planning is next automated using the novel Planar Image-Space Trajectory (PIST) planning algorithm, which uses computer vision alone to generate machining trajectories. The PIST algorithm is completely automated, with no required CAD data of the workpiece, adapting to new workpieces or manufacturing imperfections. The feasibility of the PIST algorithm is investigated through robotic deburring experimentation, where it successfully deburred the sheet metal parts. The PIST algorithm proved to be the preferred candidate over the PCAT algorithm, as it provided an indistinguishable resulting surface finish while reducing the setup time.

First International Conference on Innovative Computing, Information and Control - Volume I (ICICIC'06)

“…The surface tracking based on force guiding are studied better [7] . For example, S. Ahmad and C.N.Lee [8] studied the shape recovery of an unknown planar contour present in the robot workspace.…”

Section: Introductionmentioning

confidence: 99%

Investigation on Human-Simulation Intelligent Control of the Touch Force in Remote Welding Teleteaching

Liu

Gao

Zhang

et al.

In remote welding teleteaching process (RWTP), some factors, such as the high-frequency interference ,the vibration of the robot arm, the change of the actual gravity center of welding tracing probe produced by the change of robot space posture ,and the roughness of the welding groove, etc. This may strongly interfere with the force signal, reduce the reliability of touch force signal transmission, distort the force telepresence of welding operator, and consequently influence remote welding teleteaching quality. The paper, by analyzing force error target track on the foundation of the PID control model, brings forward human-simulation intelligent control(HSIC) strategy based on the force guiding. Its characteristic algorithm is established ,including the characteristic model, characteristic identification, characteristic memory, multi-model control and multitarget decision-making. The experimental results show that the force error between fact phase track and idea phase track is lessened , the oscillating scope of touch force obviously reduced ,the stability time of RWTP shortened, the efficiency and playback precision of the RWTP improved by comparing HSIC with PID control.