A review of the trajectory planning of Industrial robots
DOI:
https://doi.org/10.62051/4dte6t19Keywords:
Industrial Robots;Trajectory Planning ;Industrial Field Application Scenarios.Abstract
With the continuous extension of the application scenarios of industrial robots, industrial robots have made great contributions to increase productivity and automation in the industrial field. And trajectory planning of industrial robots is the key link for its successful completion of tasks. In order to deeply analyze the mechanism of trajectory planning of industrial robots, this paper firstly introduces the principle of trajectory optimization. And then it reviews the relevant theories and methods of trajectory planning. Finally, it summarizes the development trend of trajectory planning of industrial robots.
Downloads
References
[1] Shi Xin, Liao Liang, Song Wei, Xu Shuyuan. A trajectory planning method based on feed forward compensation and quintic polynomial interpolation[C]. 2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI), 2019
[2] Siciliano B, Oussama K. Springer handbook of robotics[M]. Berlin: Springer-Verlag, 2008: 27-29.
[3] Kroger T. On- line trajectory generation in robotic systems[M]. Berlin: Springer-Verlag, 2010: 12-22
[4] Haihua Mu, Yunfei Zhou, Sijie Yan et al. Precision control of third-order trajectory planning for ultra-precision point-to-point motion [J]. Journal of Mechanical Engineering, 2008, 44(1): 126-132.
[5] Gurjeet Singh, Vijay Kumar Banga. Combinations of novel hybrid optimization algorithms based trajectory planning analysis for an industrial robotic Manipulators[J]. Journal of Field Robotics,2022, 39:650-674
[6] Boryga M, Grabo´s A (2009) Planning of manipulator motion trajectory with higher-degree polynomials use[J]. Mech Mach Theory,2009,44(7):1400–1419
[7] Jing Yang, Yingjie Gao, Rui Guo, Qingshan Gao, Jingyi Zhao. Research on Excavator Trajectory Control Based on Hybrid Interpolation [J]. Sustainability 2023, 15:1-21
[8] Ruoyu Xu, Jianyan Tian, Jifu Li, Xinpeng Zhai. Trajectory Planning of Rail Inspection Robot Based on an Improved Penalty Function Simulated Annealing Particle Swarm Algorithm[J]. International Journal of Control, Automation, and Systems 2023, 21: 3368-3381
[9] Yong-Lin Kuo, Chun-Chen Lin, Zheng-Ting Lin. Dual-optimization trajectory planning based on parametric curves for a robot manipulator[J]. International Journal of Advanced Robotic Systems ,2020,2:1-14
[10] Zhenyu Yang. Research on trajectory planning method for mining robot based on NURBS curve [D]. Zhejiang University, 2020
[11] Qian Zhang. Trajectory planning and parameter optimization of six-degree-of-freedom swing feeding robot [D]. Jinan University, 2020
[12] Huang J, Hu P, Wu K, Zeng M (2018) Optimal time-jerk trajectory planning for industrial robots[J]. Mech Mach Theory 121:530–544.
[13] Gasparetto A, Zanotto V. Optimal trajectory planning for industrial robots[J]. Advances in Engineering Software, 2010 (41): 548-556
[14] Wang M, Luo J, Yuan J, Walter U. Coordinated trajectory planning of dual-arm space robot using constrained particle swarm optimization[J]. Acta Astronaut,2018, 146:259–272.
[15] Jianjun Yao, Yuxuan Huang, Zhenshuai Wan, Le Zhang, Cheng Sun, Xiaodong Zhang. Minimum-time trajectory planning for an inchworm-like climbing robot based on quantum-behaved particle swarm optimization[J]. Journal of mechanical engineering science, 2016, 4:1-12
[16] Karahan, O., Karci, H. & Tangel, A. Optimal trajectory generation in joint space for 6R industrial serial robots using cuckoo search algorithm. Intel Serv Robotics 15, 627–648 (2022). https://doi.org/10.1007/s11370-022-00440-8
[17] Elias K. Xidias. Time-optimal trajectory planning for hyper-redundant manipulators in 3D workspaces[J]. Robotics and Computer-Integrated Manufacturing, 2018, Volume 50, doi: https://doi.org/10.1016/j.rcim.2017.10.005.
[18] Yongkang Niu.Research on optimal trajectory planning time for 6-DOF serial robots[D]. Changchun University of Technology, 2013
[19] Pires E J S, Tenreiro M, Oliveira M.Robot trajectory planning using multi-objective genetic algorithm optimization [J]. Lecture Notes in Computer Science-GECCO, 2004, 24(5): 33-38.
[20] John Gregory, Alberto Olivares, Ernesto Staffetti. Energy-optimal trajectory planning for robot manipulators with holonomic constraints[J]. Systems & Control Letters,2012,61:279-291
[21] Hsien-I Lin. A Fast and Unified Method to Find a Minimum-Jerk Robot Joint Trajectory Using Particle Swarm Optimization[J]. Journal of intelligence robot system,2014,75:379-392
[22] Jing Wu, Huapeng Wu, Yuntao Song, Yong Cheng, Wenglong Zhao, Yongbo Wang. Genetic algorithm trajectory plan optimization for EAMA: EAST Articulated Maintenance Arm[J]. Fusion Engineering and Design,2016:1-7
[23] Haojie Zhang, Yudong Zhang, Chuankai Liu, Zuoyu Zhang. Energy efficient path planning for autonomous ground vehicles with Ackermann steering[J]. Robotics and Autonomous Systems, 2023, 162:1-11
Downloads
Published
Conference Proceedings Volume
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
