Published November 30, 2023 | Version CC-BY-NC-ND 4.0
Journal Open

Obstacle Avoidance Trajectory Planning for Robotic Arm based on Genetic Algorithm

Creators

  • 1. School of Mechanical Engineering, Anhui University of Science and Technology, China.

Contributors

Contact person:

  • 1. School of Mechanical Engineering, Anhui University of Science and Technology, China.
  • 2. School of Mechanical Engineering, Anhui University of Science and Technology, School of Artificial Intelligence, Anhui University of Science and Technology, China.
  • 3. School of Computer science and Engineering, Anhui University of Science and Technology, China.

Description

Abstract: For the problem of obstacle avoidance trajectory planning of a robot arm, a robot arm obstacle avoidance method based on a genetic algorithm is proposed. It is based on the two problems that the motion process can avoid obstacles and the motion process is more stable and efficient. First, the motion of each joint is planned as a sixth-degree polynomial, and the coefficients of the sixth-degree term are set as the pending parameters, and the motion of each joint is changed by changing the pending parameters. Then, the fitness function is then constructed by calculating the collision detection, angular velocity limit detection, acceleration limit detection, and the total trajectory length and rotation angle for each joint. Finally, the fitness function is optimised using a genetic algorithm to obtain smooth, continuous, and collision-free trajectories. Matlab simulation experiments show that this method can obtain the optimal or suboptimal trajectory without collision.

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Additional details

Identifiers

DOI
10.35940/ijrte.D7946.1112423
ISSN
2277-3878

Dates

Accepted
2023-11-15
Manuscript received on 11 October 2023 | Revised Manuscript received on 14 November 2023 | Manuscript Accepted on 15 November 2023 | Manuscript published on 30 November 2023

References

  • JIA Qingxuan, CHEN Gang, SUN Hanxu, ZHENG Shuangqi. Obstacle avoidance path planning for spatial robotic arm based on A~* algorithm[J]. Journal of Mechanical Engineering,2010,46(13):109-115. https://doi.org/10.3901/JME.2010.13.109
  • Chen Jinfeng, Huang Weihua, Zhang Zheng, Li Legend. Path planning algorithm based on improved artificial potential field method in dynamic environment[J]. Combined machine tools and automated machining technology,2020(12):6-9+14.
  • ADELI Hossein,TABRIZI M H N,MAZLOOMIAN Alborz.et al.Path Planning for Mobile Robots Using Iterative Artificial Potential Field Method[J]. International Journal of Computer Science Issue,2011,8( 44) : 28-32
  • Biyun Xie,Jing Zhao,Yu Liu. Motion planning of 7R robotic arm obstacle avoidance reach point based on fast extended random tree[J]. Journal of Mechanical Engineering,2012,48(03):63-69. https://doi.org/10.3901/JME.2012.03.063
  • VERAS Lgdo,MEDEIROS Fll,GUIMARAES Lnf. Rapidly Exploring Random Tree with a Sampling Method Based on Sukharev Grids and Convex Vertices of Safety Hulls of Obstacles,[J],International Journal of Advanced Robotic Systems,2019,16( 1) : https://doi.org/10.1177/1729881419825941
  • Jiaojiao Wang,Jianlin Mao. Mobile robot path planning based on improved ant colony algorithm in dynamic environment[J]. Information and Communication Technology,2019,13(05):28-32.
  • QI Ruolong, ZHOU Weijia, WANG Tiejun. A spatial robotic arm obstacle avoidance trajectory planning method based on genetic algorithm[J]. Robotics,2014,36(03):263-270.
  • Ma Yuhao, Liang Yanbing. A robot arm obstacle avoidance algorithm based on sixth degree polynomial trajectory planning[J]. Journal of Northwestern Polytechnical University,2020,38(02):392-400. https://doi.org/10.1051/jnwpu/20203820392
  • by W. F. Xu, B. Liang. Redundant space robot manipulator arm Kinematics, trajectory planning and control [M]. [Science Press]. [2017.11]. [336 pp]. [14345225]
  • Adapting Best Path for Mobile Robot By Predicting Obstacle Size. (2019). In International Journal of Innovative Technology and Exploring Engineering (Vol. 8, Issue 9S2, pp. 200–202). https://doi.org/10.35940/ijitee.i1039.0789s219
  • Mujtaba, H., Singh, G., & Gupta, P. (2019). Safe Path Planning of Mobile Robot in a known Dynamic Environment. In International Journal of Engineering and Advanced Technology (Vol. 9, Issue 2, pp. 2434–2439). https://doi.org/10.35940/ijeat.b3904.129219
  • Venkatesh, K., & Purushotham. (2019). A Versitile Method to Design a Three Fingered Robotic Arm using Cad and Matlab Technique. In International Journal of Recent Technology and Engineering (IJRTE) (Vol. 8, Issue 4, pp. 308–310). https://doi.org/10.35940/ijrte.d6818.118419
  • Chitroda, M., & Patle, Dr. B. K. (2023). A Review on Technologies in Robotic Gripper. In International Journal of Advanced Engineering and Nano Technology (Vol. 10, Issue 5, pp. 1–5). https://doi.org/10.35940/ijaent.c7232.0511523
  • Rathi, Mr. N. (2020). Study on Ai Performance and Possibilities for Future Wars. In International Journal of Management and Humanities (Vol. 5, Issue 2, pp. 41–45). Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP. https://doi.org/10.35940/ijmh.l1087.105220