An Intelligent Path Generation Method of Robotic Grinding for Large Forging Parts

Author:

Yan Shouxin,Wang Qilong,Su Pengfei,Wang Wei

Publisher

Springer International Publishing

Reference10 articles.

1. Kafle, A., Shrestha, P.L., Chitrakar, S., et al.: A review on casting technology with the prospects on its application for hydro turbines. J. Phys. Conf. Ser. 1608 (2020)

2. Prabhakar, A., Papanikolaou, M., Salonitis, K., Jolly, M., et al.: Minimising defect formation in sand casting of sheet lead: a DoE approach. Metals-Open Access Metall. J. 10(2), 252 (2020)

3. Zhang, M., Chen, T., Tan, Y., et al.: An adaptive grinding method for precision-cast blades with geometric deviation. Int. J. Adv. Manuf. Technol. (3) (2020)

4. Xiao, W., Liu, G., Zhao, G.: Generating the tool path directly with point cloud for aero-engine blades repair. Proc. Inst. Mech. Eng. 235(5) (2021)

5. Di, D., Polden, J., Dong, J., et al.: Sensor guided robot path generation for surface repair tasks on a large scale buoyancy module. IEEE/ASME Trans. Mechatron. 23(2), 636–645 (2018)

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1. Point cloud-based model-free path planning method of robotic grinding for large complex forged parts;The International Journal of Advanced Manufacturing Technology;2024-07-02

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