MagMites - Microrobots for wireless microhandling in dry and wet environments
Dominic R. Frutiger, Bradley E. Kratochvil, Bradley J. Nelson
- 发表年份
- 2010
- 引用次数
- 10
摘要
Central to the challenge of building sub-mm robots, or microrobots, is the development of effective power storage and locomotion mechanisms. In 2007 we introduced the Wireless Resonant Magnetic Micro-actuator (WRMMA) and its application in a successful microrobotic platform, the MagMite. The term MagMite is derived from Magnetic Mite-a tribute to the underlying magnetic propulsion principle and the microscale dimensions of the robot. The device harvests magnetic energy from the environment and effectively transforms it into impact-driven mechanical force while being fully controllable. It can be powered and controlled with oscillating fields in the kHz range and strengths as low as 2 mT, which is only roughly 50 times the average earth magnetic field. These microrobotic agents with dimensions less than 300 μm × 300 μm × 70 μm are capable of moving forward, backward and turning in place while reaching speeds in excess of 12.5 mm/s or 42 times the robot's body length per second. The robots produce enough force to push micro-objects of similar sizes and can be visually servoed through a maze in a fully automated fashion. The devices exhibit an overall degree of flexibility, controllability and performance unmatched by other microrobots reported in the literature. The robustness of the MagMites leads to high experimental repeatability, which in turn enabled them to successfully compete in the RoboCup 2007 and 2009 Nanogram competitions. In this video contribution we offer an integrated explanation of the non-intuitive MagMite actuation principle. This is achieved with the help of computer animation in direct comparison with real experimental footage. Furthermore, new recordings of the microrobots operating under dry and wet conditions while performing automated microhandling tasks are presented.
关键词
相关论文
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