Small-scale robots have great potential in medicine, micro-assembly and many other areas. For example, robots containing iron can be steered using the magnetic gradient generated by MRI scanners. Since the gradient is approximately the same everywhere inside the scanner, each robot receives the same input and therefore they all are subjected to the same force. A similar technique can be used with rotating magnetic fields. Each robot receives the same inputs, making motion planning challenging. This paper uses a Rapidly Exploring Random Tree (RRT) to plan paths that deliver multiple robots to goal positions by using obstacles to break the actuation symmetry.
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Magnetic Hammer Actuation for Tissue Penetration using a Millirobot
Untethered magnetic navigation of millirobots within a human body using a magnetic resonance imaging (MRI) scanner is a promising technology for minimally invasive surgery or drug delivery. Because MRI scanners have a large static magnetic field, they cannot generate torque on magnetic millirobots and must instead use gradient-based pulling. However, gradient values are too small to produce forces large enough to penetrate tissue. This letter presents a method to produce large pulsed forces on millirobots. A ferromagnetic sphere is placed inside a hollow robot body and can move back and forth. This movement is created by alternating the magnetic gradient direction. On the posterior side, a spring allows the sphere to change direction smoothly. On the anterior side, a hard rod creates a surface for the sphere to impact. This impact results in a large pulsed force. The purpose of this study was to understand the functioning of magnetic hammer actuation and control, as well as demonstrate the viability of this mechanism for tissue penetration. This letter begins with modeling and simulating this system. Next, different control strategies are presented and tested. The system successfully penetrated lamb brain samples. Finally, preliminary tests inside a clinical MRI scanner demonstrate the potential of this actuation system.
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- Award ID(s):
- 1646566
- PAR ID:
- 10048934
- Date Published:
- Journal Name:
- IEEE Robotics and Automation Letters
- ISSN:
- 2377-3774
- Page Range / eLocation ID:
- 1 to 1
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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