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Control system for automatic search and transportation of an object by a mobile robot with obstacle avoidance function

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Abstract

In this paper, using image processing and distance measurement, we develop a control system for automatic gras** and obstacle avoidance by a mobile robot. First, the mobile robot searches an object by turning until it is captured in camera image. Next, the mobile robot approaches the object. If an obstacle exists, the mobile robot avoids the obstacle by a specific movement. After avoiding the obstacle, the mobile robot turns again to search for the object. When the mobile robot approaches the target sufficiently, it grasps or releases the object. The usefulness of the control system was verified through experiments.

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References

  1. Matsuda Y, Sugi T, Goto S, Egashira N (2017) Teleoperation system for a mobile robot with visual servo mechanism based on automatic template generation. Artif Life Robot 22(4):490–496

    Article  Google Scholar 

  2. Matsuda Y, Tagami N, Sugi T, Goto S, Egashira N (2018) Teleoperation system for a mobile robot with visual servomechanism based on turning radius determination using angle information of image. Artif Life Robot 24(1):106–113

    Article  Google Scholar 

  3. Matsuda Y, Sato Y, Sugi T, Goto S, Egashira N (2021) Control system for object grip** by mobile robot with object gras** arm by combining manual operation with visual servoing. Int J Innov Comput Inf Control 17(6):2081–2092

    Google Scholar 

  4. Matsuda Y, Sato Y, Sugi T, Goto S, Egashira N (2022) Control system for object transportation by a mobile robot with manipulator combined with manual operation and automous control. Int J Innov Comput Inf Control 18(2):621–631

    Google Scholar 

  5. Matsuda Y, Sato Y, Sugi T, Goto S, Egashira N (2021) Control system for automatic search and transportation of an object by a mobile robot using image processing. Artif Life and Robot 26(4):465–472

    Article  Google Scholar 

  6. Sudhakara P, Ganapathy V, Priyadharshini B, Sundaran K (2018) Obstacle avoidance and navigation planning of a wheeled mobile robot using amended artificial potential field method. Proc Comput Sci 133:998–1004

    Article  Google Scholar 

  7. Kubota T, Hashimoto H (1990) A strategy for collision avoidance among moving obstacles for a mobile robot, IFAC Proceedings Volumes, Vol. 23, No. 8. Part 5:105–110

  8. **Yoo S (2013) Adaptive neural tracking and obstacle avoidance of uncertain mobile robots with unknown skidding and slip**. Inf Sci 238:176–189

    Article  MATH  Google Scholar 

  9. Mondal S, Ray R, Reddy S, Nandy S (2022) Intelligent controller for nonholonomic wheeled mobile robot: a fuzzy path following combination. Math Comput Simul 193:533–555

    Article  MATH  Google Scholar 

  10. Kubota T, Hashimoto H (2021) An obstacle avoidance algorithm for robot manipulators based on decision-making force. Robot Compu-Integr Manuf 71:102114–102128

    Article  Google Scholar 

  11. Abiyev R, Ibrahim D, Erin B (2010) Navigation of mobile robots in the presence of obstacles. Adv Eng Softw 41:1179–1186

    Article  MATH  Google Scholar 

  12. Solea R, Cernega D (2012) Obstacle Avoidance for Trajectory Tracking Control of Wheeled Mobile Robots, Proceedings of the 14th IFAC Symposium on Information Control Problems in Manufacturing Bucharest, Romania, May 23–25, pp 906–911

  13. Mohanta J, Keshari A (2019) A knowledge based fuzzy-probabilistic roadmap method for mobile robot navigation. Appl Soft Comput J 79:391–409

    Article  Google Scholar 

  14. Agarwal D, Bharti P (2021) Implementing modified swarm intelligence algorithm based on Slime moulds for path planning and obstacle avoidance problem in mobile robots. Appl Soft Comput 107:107372–107386

    Article  Google Scholar 

  15. Bernardini F, Silva M, Abe J (2021) Application of Paraconsistent Annotated Evidential Logic \(E\tau\) for a Terrestrial Mobile Robot to Avoid Obstacles. Proc Comput Sci 192:1821–1830

    Article  Google Scholar 

  16. Gharajeh M, Jond H (2022) An intelligent approach for autonomous mobile robots path planning based on adaptive neuro-fuzzy inference system. Ain Shams Eng J 13:101491–101501

    Article  Google Scholar 

  17. Das M, Sanyal S, Mandal S (2022) Navigation of Multiple Robots in Formative Manner in an Unknown Environment using Artificial Potential Field Based Path Planning Algorithm. Ain Shams Eng J 13:101675–101689

    Article  Google Scholar 

  18. Fairchild P, Srivastava V, Tan X (2021) Efficient Path Planning of Soft Robotic Arms in the Presence of Obstacles. IFAC PapersOnLine 54(20):586–591

    Article  Google Scholar 

  19. Matamoros M, Seib V, Memmesheimer R, Paulus D (2018), RoboCup@Home: summarizing achievements in over eleven years of competition. Proceedings of the IEEE International Conference on Autonomous Robot Systems and Competitions, pp. 186-191

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Correspondence to Yoshitaka Matsuda.

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Matsuda, Y., Wada, Y., Sugi, T. et al. Control system for automatic search and transportation of an object by a mobile robot with obstacle avoidance function. Artif Life Robotics 28, 236–243 (2023). https://doi.org/10.1007/s10015-022-00817-z

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  • DOI: https://doi.org/10.1007/s10015-022-00817-z

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