Jumping Silicon Microrobots With Electrostatic Inchworm Motors and Energy Storing Substrate Springs

Abstract: 

Jumping microrobots are a burgeoning area of autonomous microelectromechanical systems (MEMS). This dissertation presents background, theory, designs, and results of the first jumping microrobots fabricated in a silicon-on-insulator (SOI) process using electrostatic inchworm motors etched into the device layer silicon and energy storing springs etched into the silicon substrate. Substrate silicon is much thicker than device layer silicon, and can therefore store a lot more mechanical energy per unit area than can device layer silicon. New high force density electrostatic inchworm motors designed to stretch and store energy in substrate springs are presented.

The first ever SOI robot to use electrostatic inchworm motors to store energy in a substrate spring is presented. While this robot was unable to use its electrostatic inchworm motors to store enough energy to jump, it was able to store enough energy to kick both a 0.6 milligram 0402 capacitor and a 2.5 gram mass (which weighed more than 25 times that of the robot). Additionally, the robot was able to vertically jump 4cm when its substrate spring was manually compressed with tweezers. A redesigned robot is then presented which used its on-board electrostatic inchworm motor to store energy in its substrate spring and vertically jump 3.6mm. To date, this is the highest jumping SOI based microrobot as well as the only one to store mechanical energy in substrate silicon.

Finally, steps towards integration of the robot with a CMOS brain and high voltage solar cells for full autonomy is presented, along with design improvements needed to achieve a one meter high vertical jump.

Publication date: 
May 27, 2020
Publication type: 
Ph.D. Dissertation
Citation: 
%0 Thesis %A Schindler, Craig %T Jumping Silicon Microrobots With Electrostatic Inchworm Motors and Energy Storing Substrate Springs %I EECS Department, University of California, Berkeley %D 2020 %8 May 27 %@ UCB/EECS-2020-73 %U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-73.html %F Schindler:EECS-2020-73