Kristofer S.J. Pister (Advisor)

Research Advised by Professor Kristofer S.J. Pister

Pister Group:  List of Projects | List of Researchers

Wentian Mi

Graduate Student Researcher
Electrical Engineering and Computer Sciences
Professor Michel M. Maharbiz (Advisor)
Professor Kristofer S.J. Pister (Advisor)
Ph.D. 2023 (Anticipated)

BSAC's Best: Fall 2022 Awards Announced

September 28, 2022

BSAC would like to thank all of the researchers who presented their research during BSAC's Fall 2022 Research Review on September 21st.

BSAC Industrial Members voted for the outstanding paper and presentations and the results are in. Please join BSAC in congratulating the recipients of the Fall 2022 Best of BSAC honors, Alex Moreno, Mutasem Odeh, and Vivian Wang!

Outstanding Presenter...

BPN959: Self-Righting for Micro Robots

Alexander Alvara

In developing micro-robots for exploration in non-uniform terrain, it is often the case that robots fall over. This work seeks to provide a solution in the self-righting of autonomous micro-robots to overturn a 1cc, 1 gram cube microrobot with regular octahedral symmetry that has fallen on either of its four sides and overturning said microrobot once upside down. Our design currently consists of a 3-bar linkage in conjunction with an electrostatic inchworm motor. First-generation devices are in fab as of August. Hand analysis indicates that self-righting from any face should be...

BPN857: Miniature Autonomous Rockets

Alexander Alvara

Pico air vehicles (PAVs), sub-5cm aerial vehicles, are becoming more feasible due to advances in wireless mesh networks, millimeter-scale propulsion, battery technology, and MEMS control surfaces. Our goal is to develop an aerodynamic MEMS control surface that could be used in PAV applications. This device will use electrostatic inchworm motors (capable of outputting 15mN) to extend an airfoil through 10 degrees. Using information from previous work that demonstrated roll control, we expect to extend automated flight control to pitch and yaw. We predict and output torque of 2.3 uNm,...

BPN890: Hydrogel Actuated Carbon Fiber Microelectrode Array

Oliver Chen

Glial scarring and passivization of long-term implanted neural probes is one bottleneck in brain- machine interface technology. However, ultraflexible probes with similar mechanical properties as tissue have been shown to minimize scarring and other biological responses. We propose a flexible, microscale neural probe that can be actuated using an expanding hydrogel. This device is designed to be able to record neural signals up to hundreds of microns away from the insertion site. This design can allow for high-density, accurate neural recordings for a wide variety of clinical applications...

BPN969: Joule Bonding: Localized Solder Bonding for Heterogenous Integration of MEMS

Daniel Teal

We are developing a new MEMS bonding process in which we use extremely carefully controlled resistive heating to make a solder bond with negligible substrate temperature rise and tighter temperature control than in laser bonding; we do this by using the temperature change of the heater resistivity as a temperature sensor for closed-loop control. Previously, we analyzed transient heat flow and showed initial progress toward heater control. Now, we have completed our theoretical analysis with a description of temperature fluctuations due to local inhomogeneities on the chip and how to...

Single-Chip Micro Mote in EEG, fMRI, and TMS Systems

Joshua Alexander
Kristofer S.J. Pister

The goal of this project is to measure EEG signals in an MRI during TMS and report the EEG measurements wirelessly. The opportunities combining SoC-based devices with cutting-edge technology are rapidly expanding. A Single Chip Micro-Mote (SCμM) that has been developed as an ultra-small crystal-free SoC opens up the door of possibilities even more. Similarly, brain stimulation and measurement has taken a leap forward as Transcranial Magnetic Stimulation (TMS), Electroencephelography (EEG), and functional Magnetic Resonance Imaging (fMRI) have grown in popularity. A structure that...

Synergy of Prediction and Control in Model-based Reinforcement Learning

Nathan Lambert

Model-based reinforcement learning (MBRL) has often been touted for its potential to improve on the sample-efficiency, generalization, and safety of existing reinforcement learning algorithms. These model-based algorithms constrain the policy optimization during trial-and-error learning to include a structured representation of the environment dynamics. To date, the posited benefits have largely been left as directions for future work. This thesis attempts to illustrate the central mechanism in MBRL: how a learned dynamics model interacts with decision making. A better understanding of...

BPN930: Robust MEMS Inchworm Motors

Daniel Teal
Dillon Acker-James
Alex Moreno
Alexander Alvara

We are developing robust, high force, low power, and efficient MEMS inchworm motors for microrobots. So far, we have created 3x4.7mm motors in a 40um SOI process capable of linearly actuating a shuttle with 15mN force and 5mm/s travel at < 1mW power draw to > 50mm displacement. By integrating these motors into 550um thick reinforcing silicon substrate structures we created a microgripper capable of reliably lifting 1g weights and other macroscopic objects. We also showed gripper operation off solar power in BSAC project BPN873. Finally, we have analyzed motor efficiency, an...