A new calibration method for a dynamic coordinate system in a robotic blade grinding and polishing system based on the six-point limit principle

Zhu, Guangshan; Cai, Ming; Wang, Zhengjia; Li, Lun; Zhao, Jibin; Zhang, Bo

doi:10.1016/j.rcim.2023.102561

Cited by 7 publications

(2 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, the calibration of industrial robots when the robot is operated at high speeds will also be considered. Contact approaches for industrial robot calibration [ 43 , 44 ] are usually lower-cost approaches for estimating more precise DH parameters of industrial robots. Motion sensors are another type of sensor which have already contributed to the precise calibration of industrial robots [ 45 , 46 ].…”

Section: Future Workmentioning

confidence: 99%

Precision Denavit–Hartenberg Parameter Calibration for Industrial Robots Using a Laser Tracker System and Intelligent Optimization Approaches

Khanesar

Yan

Isa

et al. 2023

Sensors

View full text Add to dashboard Cite

Precision object handling and manipulation require the accurate positioning of industrial robots. A common practice for performing end effector positioning is to read joint angles and use industrial robot forward kinematics (FKs). However, industrial robot FKs rely on the robot Denavit–Hartenberg (DH) parameter values, which include uncertainties. Sources of uncertainty associated with industrial robot FKs include mechanical wear, manufacturing and assembly tolerances, and robot calibration errors. It is therefore necessary to increase the accuracy of DH parameter values to reduce the impact of uncertainties on industrial robot FKs. In this paper, we use differential evolution, particle swarm optimization, an artificial bee colony, and a gravitational search algorithm to calibrate industrial robot DH parameters. A laser tracker system, Leica AT960-MR, is utilized to register accurate positional measurements. The nominal accuracy of this non-contact metrology equipment is less than 3 μm/m. Metaheuristic optimization approaches such as differential evolution, particle swarm optimization, an artificial bee colony and a gravitational search algorithm are used as optimization methods to perform the calibration using laser tracker position data. It is observed that, using the proposed approach with an artificial bee colony optimization algorithm, the accuracy of industrial robot FKs in terms of mean absolute errors of static and near-static motion over all three dimensions for the test data decreases from its measured value of 75.4 μm to 60.1 μm (a 20.3% improvement).

show abstract

Section: Future Workmentioning

confidence: 99%

Precision Denavit–Hartenberg Parameter Calibration for Industrial Robots Using a Laser Tracker System and Intelligent Optimization Approaches

Khanesar

Yan

Isa

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…Jia et al established a 3D model of a grinding workstation and designed the arc grinding trajectory of blade rear, providing theoretical guidance for the high-precision prediction of material removal during turbine blade surface grinding[14]. Zhu et al introduced the concept of six-point positioning into the dynamic workpiece coordinate frame calibration process using a point laser displacement sensor (PLDS), achieving higher precision calibration results and improving operational efficiency[15]. Based on the conformal contact and Hertz theory, Wu et al demonstrated, through finite element simulation and static pressure experiments, that multiple concentrated forces are are the best grinding pressure loading mode[16].…”

mentioning

confidence: 99%

Point Cloud Based Model-free Path Planning Method for grinding Large Complex Forging Parts

Yan,

Wang,

et al. 2023

Preprint

View full text Add to dashboard Cite

Large and complex forgings, serving as crucial load-supporting components in the fields of energy, ships, transportation, etc., demand high dimensional accuracy and surface quality during post-processing. The automation of grinding for such large and complex forgings presents a common and pressing challenge within the forging industry. One of the main obstacles lies in the substantial thermal deformation and various random forging defects, making the automatic generation of grinding paths a difficult task. In this paper, we propose an algorithm for identifying random defects in large and complex forgings. By combining the RANdom Sample Consensus (RANSAC) algorithm with the Modified Iterative Closest Point (M-ICP) algorithm, we register the standard component point cloud with the forging point cloud, thereby obtaining the point cloud representing the random defects that require grinding. Subsequently, we classify the random defect point cloud based on defect area size and establish a strategy for generating grinding paths. Utilizing the positional coordinate information within the random defect point cloud, we directly generate robot grinding paths without relying on a CAD model. Finally, we conduct robot grinding experiments on large and complex forgings. The experimental results demonstrate that the model-free generation method for grinding paths accurately identifies the characteristics of random forging defects, efficiently plans robot grinding paths, and significantly improves grinding efficiency and quality. This approach offers an intelligent solution for the post-processing of large and complex forgings.

show abstract

Point cloud-based model-free path planning method of robotic grinding for large complex forged parts

Yan,

Wang,

et al. 2024

Int J Adv Manuf Technol

View full text Add to dashboard Cite

A new calibration method for a dynamic coordinate system in a robotic blade grinding and polishing system based on the six-point limit principle

Cited by 7 publications

References 14 publications

Precision Denavit–Hartenberg Parameter Calibration for Industrial Robots Using a Laser Tracker System and Intelligent Optimization Approaches

Precision Denavit–Hartenberg Parameter Calibration for Industrial Robots Using a Laser Tracker System and Intelligent Optimization Approaches

Point Cloud Based Model-free Path Planning Method for grinding Large Complex Forging Parts

Point cloud-based model-free path planning method of robotic grinding for large complex forged parts

Contact Info

Product

Resources

About