Micro-force Sensing Mobile Microrobots (μFMMs)

Filed in Research by on September 26, 2014 • views: 2361

This project is on the creation of a novel class of magnetically-controlled, mobile microrobots with two-dimensional vision-based micro-force sensing end-effectors. By combining advanced mobile manipulation microrobots with a MEMS-based micro-force sensor, a novel, transformative tool for future advancements in mechanobiology and automated biomanipulation will result. The end-effectors of the mobile microbots consist of micro-compliant mechanisms with custom-designed force-deflection characteristics whose deformations are observed with a camera attached to an optical microscope. They are fabricated along with a magnetic microrobot body and are therefore controllable with external magnetic field gradients. These micro-force sensing mobile microrobots will have real-time micro-force-control manipulation capabilities specifically tailored for mechanobiology and automated biomanipulation tasks. A portable Bio-Robotics test-bed, designed to fit comfortably around both inverted optical or confocal microscopes is also under development. A series of proof-of-concept application studies related to single cell and biomaterial adhesion and cell characterization are planned to showcase the efficacy of the system.

Grants: NSF, ONR
Students: Wuming Jing, Peter Jaron, Archit Agarwal
Selected Publications

  1. W. Jing, D. Cappelleri, “A Magnetic Microrobot with In-situ Force Sensing Capabilities”, Special Issue: The Frontiers of Micro and Nanorobotic Systems, Robotics, Vol. 3, Issue 2, pp. 106-119, 2014.
  2. W. Jing, D. Cappelleri, “Incorporating In-situ Force Sensing Capabilities in a Magnetic Microrobot”, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Chicago, IL USA, September 14-18, 2014.
  3. W. Jing, D. Cappelleri, “Towards Functional Mobile Magnetic Microrobotics”, I. Proprotny, S. Bergbreiter (Eds.), Chapter in Small Scale Robotics: From Nano-to-Millimeter-Sized Robotic Systems and Applications, Lecture Notes in Computer Science, Volume 8336, 2014, pp 81-100.