Development of an Untethered Ultrasonic Robot With Fast and Load-Carriable Movement Imitating Rotatory Galloping Gait
Jiang Wu, Zhaochun Ding, Lipeng Wang, Ranxu Zhang, Yanhu Zhang, Xuewen Rong, Rui Song, Huijuan Dong, Jie Zhao, Yibin Li
- Year
- 2024
- Citations
- 14
Abstract
An untethered ultrasonic robot (U2sonobot) operating in resonant vibration is developed by integrating dual transducers, an onboard circuit, and a battery. Here, the longitudinal and bending vibrations lead to the out-of-phase swing motion and the alternating acceleration, respectively; these imitate the rotatory galloping gait in terms of the driving feet's movement pattern and the operating sequence. First, the transducers were designed to gather the resonant frequencies of two vibrations and produce the same node for steadily supporting the other components. Second, an onboard circuit was devised to convert the 3.7 V battery's dc signal into multi-channels of ultrasonic signals via multilevel amplification. Third, a prototype 54 × 52 × 46 mm3 in size and 76.5 g in weight was fabricated to assess its moving/carrying performance. At 59.3 kHz frequency, U2sonobot yielded the maximal speed of 221 mm/s and the minimal step displacement of 0.3 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</i>m. According to the wirelessly-received commands, it produced various types of flexible movements (e.g., those with adjustable speed/steering-radii and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> rotations) and climbed 8.9° slope. Moreover, it carried the maximal payload of 520 g and provided the minimal cost of transport of 3.9. U2sonobot accomplishes fast and load-carriable movements, implying its potentially applicability to optical focusing/scanning system.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002