Electronic and mechanical design of a hexapod land searching robot

Year 2020, Volume: 4 Issue: 1, 34 - 40, 15.04.2020

Talha Boz İsmail Aras Samet Kıkıcı Sezgin Ersoy

https://doi.org/10.35860/iarej.648511

Cited By: 1

Abstract

In this study, it is aimed to design a robot that can be used in fields such as land exploration, mine search, ammunition transportation, search and rescue activities in natural disasters. For this purpose, a six-legged robot was designed. The robot can move evenly in uneven terrain conditions, stop, accelerate and overcome the obstacle when it sees an obstacle. The mechanical and electronic design of the robot was realized, and a prototype was manufactured. The flexibility of the legs used in the design ensures that the robot can move more easily in field conditions. The synchronous speed and direction of the motors are controlled, and the robot moves in a balanced way. With the IP camera mounted on a Raspberry Pi, snapshots were taken from the robot. Mechanical and electronic design of six-legged robot capable of moving on uneven ground was realized. The six-legged robot was placed with three legs on the right and three legs on the left. The motors were operated simultaneously to allow the robot to move evenly. Thanks to its leg structure, it was aimed to travel in land conditions. Image control was provided on the computer with the camera placed on the robot. In this study, the program written into the electronic cards run the motors simultaneously. 

Keywords

Design, Mobile robot, Rescue, Search

References

• 1. Jennings, J., S. Whelan, G. Evans, W., F. Cooperative search and rescue with a team of mobile robots. IEEE 8th Int. Conf. on Advanced Robotics, Monterey, 1997, California, U.S.A., p. 93.
• 2. Galloway, K., C. Haynes G., C. Ilhan, B., D. Johnson A., M. Knoph, R. Lynch, G., A., Plotnick B., N. White, M. and Kodistchek D., E. X-RHex: A highly mobile hexapedal robot for sensorimotor tasks. University of Pennsylvania - Technical Reports, U.S.A. 2010, p. 3-7.
• 3. Ersoy S., Görgülü S. Computer Based Education and Progress Alternative For Electro Mechanics Lesson. Acta Mechanica et Automatica, 2009, p. 6-32.
• 4. Glasius, R. Andrzej, K. and Stan, G. Neural network dynamics for path planning and obstacle avoidance. Neural Networks, 1995, 8(1): p. 125-133.
• 5. Ma Z., Q. and Yuan, Z., R. Real-time navigation and obstacle avoidance based on grids method for fast mobile robot.,2014. Seul, Korea, p. 91-95.
• 6. Henry, P. Krainin, M. Herbst, E. Ren, X. and Fox, D. RGB-D mapping: Using depth cameras for dense 3D modeling of indoor environments.2014. Delhi, India, p. 477-491.
• 7. Yalcin, M.K., Ersoy, E. Designing autopilot system for fixed-wing flight mode of a tilt-rotor UAV in a virtual environment: X-Plane. International Advanced Researches and Engineering Journal, 2018. 2(1): p. 33-42.
• 8. Saranli, U. Buehler, M. and Koditschek, D.,E. Rhex: A simple and highly mobile hexapod robot. The Int. Journal of Robotics Research, 2001. 20: p. 616-631.
• 9. Berns, K. Kepplin, V. Ilg, W. and Dillmann, R. Experiments with a stereo camera head for the local navigation of LAURON II, Forschungszentrum Informatik Karlsruhe, Germany, 1993.
• 10. RHex Robot Platform. [cited 2019 June 19]; Available from: http://www.rhex.web.tr/.
• 11. Altendorfer, R. Moore, N. Komsuoğlu, H. Buehler, M. Brown Jr. H., B., McMordie, D. Saranlı, U. Full R., J.and D. E. Koditschek. RHex: A biologically inspired hexapod runner. Autonomous Robots, 2001. 11(3): p. 207-213.
• 12. Greenfield, A. Saranli, U. and Rizzi, A., A. Solving models of controlled dynamic planar rigid-body systems with frictional contact. International Journal of Robotics Research, 2005. 24(11): p. 911-931.
• 13. Skaff, S. Rizzi, A. Choset, H. Lin. P., C. Context-Based State Estimation Technique for Hybrid Systems. Barcelona, Spain 2005. p 3935-3940.
• 14. Li, C. Zhang, T. and Goldman, D., I. A Terradynamics of Legged Locomotion on Granular Media, Science, 2013. 339 (6126) p. 1408-1412.
• 15. Jacko P. Kravets, O. Spectral Analysis by STM32 Microcontroller of the Mixed Signal. IEEE International Conference on Modern Electrical and Energy Systems. Kremenchuk, Ukraine, 2019. p 342-345.
• 16. Mao WL. Liu G.R. Chu C.T. Hung CW. Microcontroller-Based Speed Control Using Sliding Mode Control in Synchronize Reluctance Motor. Advances in Intelligent Systems and Computing, 2019.
• 17. Chaber P. Ławryńczuk, M. Fast Analytical Model Predictive Controllers and Their Implementation for STM32 ARM Microcontroller. IEEE Transactions on Industrial Informatics, 2019. p. 4580-4590.
• 18. Summary of the RHex robot platform. [cited 2019 10 June]; Available from: https://www.rhex.web.tr.