Abstract
The subsurface access technology is of great significance to study evolution of stars and probe landing, and the low velocity robotic penetrator (LVRP) is a commonly used detection technique. In this study, a novel LVRP based on ampere force (AFRP) is proposed, which uses the ampere force of the coils located in high intensity magnetic field as the driving force. The AFRP is composed of stator and mover. In the working state, the mover is subjected to a linear reciprocating motion, colliding with the stator, and displacement occurs. Firstly, parametric modeling of AFRP is carried out and the internal magnetic field distribution is analyzed. The results show that the magnetic induction between the two poles can be increased by the relative mounting of the permanent magnets, and the magnetic induction is affected by the gap and the diameter of the permanent magnets. Then, ISIGHT® software is used for integrated optimization, whose purpose is to optimize the design variables and make the output force of each unit reaches the maximum when the casing size of the AFRP is certain. Furthermore, to achieve the optimization design goal that the overall output force is maximum. According to the optimization results, the prototype was developed. The experimental results show that the AFRP operating frequency can be controlled in the range of 1 ~ 10 Hz, the average displacement of each motion cycle is 2 mm. The proposed AFRP can output a larger driving force by changing the current and the number of units. In addition, the AFRP can be used as a novel actuator for robots.
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Acknowledgments
This work is supported by Research Fund of China Manned Space Engineering (050102), the Key Research Program of the Chinese Academy of Sciences (Y4A3210301), the National Science Foundation of China (51175494, 61128008, and 51575412), and the State Key Laboratory of Robotics Foundation.
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Feng, J., Liu, J., Zhang, F. (2017). A Novel Low Velocity Robotic Penetrator Based on Ampere Force. In: Huang, Y., Wu, H., Liu, H., Yin, Z. (eds) Intelligent Robotics and Applications. ICIRA 2017. Lecture Notes in Computer Science(), vol 10464. Springer, Cham. https://doi.org/10.1007/978-3-319-65298-6_55
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DOI: https://doi.org/10.1007/978-3-319-65298-6_55
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