Opportunities

Undergrad Projects

Here are some possible undergraduate research projects (email zixiliu@g.harvard.edu if interested in any):

Muscle Classification from Ultrasound Images for Wearable Technology: This research aims to use industry-level ultrasound tools to image and classify muscles for future use with stretchable wearable sensors and wearable assistive robotics. The undergrad researcher would work on a software package to detect and annotate muscles for real-time use. By the end of the project, the developer would be familiar with ultrasound hardware, ultrasound imaging, and human anatomy. This project is ideal for applications using machine learning.
  • Skills needed: Basic programming at the level of CS50 or equivalent
  • Skills strongly preferred: Image processing / computer vision at the level of ES 143 or equivalent
  • Skills helpful: Signal processing at the levels of ES 155/156/157, BE 128 or equivalent
  • Vision-based force/torque sensors: (Low-Cost Fiducial-based 6-Axis Force-Torque Sensor): Robots need to sense the forces on the fingers to enable reliable grasping. Commercial six-axis force-torque sensors suffer from being some combination of expensive, fragile, and hard-to-use. We propose a new fiducial-based design that addresses all three points. The sensor uses an inexpensive webcam and can be fabricated using a consumer-grade 3D printer. By estimating the 3D pose of the fiducials on the sensor, we can calculate the applied force-torque. The sensor is very light and can be dropped or thrown with little concern. This approach promises to bring six-axis force-torque sensing to new applications where the precision, cost, and fragility of traditional strain-gauge based sensors are not appropriate.
  • Required skills: SolidWorks and 3D printing (ES51 is ideal preparation), Basic programming (CS50 at a minimum), Mechanical modeling (ES120 would be helpful, finite element modeling (e.g. Abaqus) also useful)
  • High-density tactile sensor design: Tactile sensing provides critical contact measurements on a robot-object system that helps make robotic grasping more reliable. However, the state of the art tactile sensors have low density, causing low spatial resolution and difficulty in contact detection at the edge of the sensory array. In this project, we aim to develop a new iteration of tactile sensors with a higher density. This includes designing a circuit board for new tactile sensor chips, fabricating into a sensor array unit, and validating its performance.
  • Required Skills: Circuits, devices, and transduction (ES152), Laboratory Electronics (Physics123 - Laboratory Electronics)
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