Summer Undergraduate Research in Engineering (SURE)

SURE offers summer research internships to outstanding current U-M undergraduate students who have completed their sophomore or junior year (preference will be given to those who have completed three years of study) by the time of their internship. Participants have the opportunity to conduct 10-12 weeks of full-time summer research with some of the country’s leading faculty in a wide range of engineering disciplines. The program provides opportunities for students to assess their interests and potential in pursuing research at the Masters or Ph.D. level in graduate school.

All participants must apply online through the SURE website. Accepted applicants receive guidance by a faculty advisor in a College of Engineering research facility, a stipend of $6,000, attend regular meetings and engage in activities that help prepare students for graduate school.

Selection Process: Eligible applications will be reviewed by department staff and provided to the Faculty Mentors, who will review your application materials for their selection. It is possible that they will reach out to you directly for further information. You do not need to do anything else or reach out to the Faculty Mentors, but if you have any specific questions regarding a SURE Project, you are welcome to reach out to the listed Faculty Mentor. Any notification of an offer will be sent from the SURE Manager. Learn more: https://sure.engin.umich.edu/

General Timeline:
January – Application opens and is due
February – Applications are reviewed
March – Offers will begin being sent out
April – Offers may still be issued during this time
May – SURE Projects may begin

The 2024 SURE application closed on January 28, 2024.

Robotics 2024 SURE Research Projects

Robotics Project #1: Mechanical Design of a Hopping Robot Leg
Faculty Mentor: Yanran Ding, yanrand@umich.edu
Prerequisites: Experience in SolidWorks, Robotics competition
Project Description: The student will design the mechanical components of a legged robot that is capable of continuous hopping motion. This project will involve design brainstorming, CAD modeling, manufacturing, robot assembly, experimental testing and data analysis.
Research Mode: In Lab

Robotics Project #2: Machine Learning for Bipedal Robot Control
Faculty Mentor: Yanran Ding, yanrand@umich.edu
Prerequisites: Experience in Python
Project Description: The student will set up machine learning environments to train locomotion controllers for a bipedal robot in a simulation environment. This project will involve exporting the robot model to the physical simulator, configuring the reward function and the tuning of the corresponding weights.
Research Mode: In Lab Robotics

Project #3: Motion Capture of Amputee Biomechanics with a Powered Prosthetic Leg
Faculty Mentor: Gregg, Robert, rdgregg@umich.edu
Prerequisites: Vicon, Matlab, Human subjects research
Project Description: The goal of this project is to assist with the motion capture data collection and analysis of an endurance study on above-knee amputees using our powered knee-ankle prosthesis. This project will be performing the data collection with the rest of the team and processing the data. Processing the data will include gap filling and filtering as well as exploring biomechanical metrics within the data. If interested and time allows, the student will be able to help with tasks outside of motion capture work. Outside of technical work, the student will be expected to attend weekly project meetings and is invited to join weekly lab group meetings.
Research Mode: In Lab Robotics

Project #4: Development and Validation of an Assistive Ankle Exoskeleton Controller
Faculty Mentor: Gregg, Robert, rdgregg@umich.edu
Prerequisites: Python, Matlab
Project Description: The goal of this project is to assist with the development and validation of a controller for an assistive, powered ankle exoskeleton for able-bodied users and users with a gait pathology or impairment. Controller development involves data-driven optimization and simulation in Matlab and real-time implementation in Python using our powered ankle exoskeleton. To validate the controller performance, the student will assist with human subject data collection and analysis, hopefully including a pilot study for users with chronic ankle arthritis. If interested and time allows, the student will be able to help with tasks outside of the ankle exoskeleton controller development and validation. Outside of technical work, the student is invited to join weekly lab group meetings.
Research Mode: In Lab Robotics

Project #5: Autonomous Navigation and MBot
Faculty Mentor: Chad Jenkins, ocj@umich.edu
Prerequisites: Robotics 102 or any Robotics 300-level course
Project Description: Robotics 102, and its focus on autonomous navigation, is a cornerstone of our trailblazing new Robotics major for undergraduates, which is poised to define robotics as an academic discipline and provide more accessible pathways for students into artificial intelligence. Further, Robotics 102 has played a central role in our efforts to realize a national model for Distributed Teaching Collaboratives — as an open-source approach to course development and building bridges between Minority Serving Institutions and R1 universities. Students working on this project will contribute to a development team focused on continued development of our MBot-series mobile robots and advancing their software stack for autonomous navigation
Research Mode: In Lab Robotics

Project #6: Control of Surgical Robots in Virtual Reality
Faculty Mentor: Mark Draelos, mdraelos@umich.edu
Prerequisites: Experience with virtual reality engines (e.g., Unreal Engine, Unity); experience programming in C++, C#, or Python
Project Description: Existing virtual reality environments for surgical use rely almost exclusively on static pre-operative image datasets, such at CT or MRI scans. This project involves developing an interactive virtual-reality environment to remotely control robot arms to perform a mock surgical procedure guided by live volumetric imaging. Potential tasks include designing 3D or virtual reality environments, implementing algorithms to transform user motions into robot movements, developing user interface strategies, and conducting studies to evaluate user performance.
Research Mode: In-Lab Robotics

Project #7: Soft Robot Face Mask
Faculty Mentor: Mark Draelos, mdraelos@umich.edu
Prerequisites: Experience with mechanical CAD (e.g., Solidworks, Inventor)
Project Description: Standard-of-care face masks require continuous application of force and healthcare provider attention in order to maintain position over the nose/mouth and avoid large leaks. This project is developing a soft robotic face mask for respiratory support that self-seals to the patient’s face without any provider intervention. Potential tasks include designing and fabricating new face prototypes, designing test protocols for masks, and performing tests of mask performance.
Research Mode: In-Lab

Robotics Project #8: Mobile Manipulation for Agricultural Applications
Faculty Mentor: Dmitry Berenson, dmitryb@umich.edu
Prerequisites: Strong programming experience (EECS 281.) Experience with robotics and/or agriculture is a plus.
Project Description: There are many farming tasks, such as pulling weeds, identifying diseases, harvesting, and applying fertilizer that could be done by robots. However, robotics lack the intelligence to do these tasks in a wide range of environments. This project will focus on developing software and algorithms for the Spot robot in order to allow it to perform farming tasks. This will include work on navigation, perception, and manipulation.
Research Mode: In Lab

Robotics Project #9: Quantifying Human Performance for Operational Environments
Faculty Mentor: Leia Stirling, leias@umich.edu
Project Description: In this interdisciplinary research group, we bring together methods from human factors, biomechanics, and robotics. We strive to understand the physical and cognitive interactions for goal-oriented human task performance and support operational decision making that relies on manual task performance. These goals may include reducing musculoskeletal injury risks, supporting telehealth, and improving technology usability. However, the term performance is not universally defined and required learning about the desired task goals and the sub-tasks and motions the human will need to accomplish them.

There are different projects students may support:

Upper Extremity Exoskeletons for Industrial Applications. Exoskeletons are currently being evaluated for many different applications. In this project, the student may support the development of a study and/or data analysis related to upper extremity exoskeletons designed to support overhead work and/or reaching and grasping.
Lower Extremity Exoskeletons for mobility assist: In this project, the student may support the development of a study and/or data analysis related to lower extremity exoskeletons designed to assist ankle motion for mobility assistance.
Space Telerobotics: In this project, the student may support the development of a simulation study and/or data analysis related to operating a small robotic satellite that inspects and docks on a simulated space station.

Research Mode: In Lab

Robotics Project #10: Development of a AR Environment for Building a Shared Mental model on Human-multi-robot interaction
Faculty Mentor: Dawn Tilbury, tilbury@umich.edu, Lionel Robert, lprobert@umich.edu
Project Description: Our research project aims to develop an augmented reality (AR) environment to study the effectiveness of collaboration between humans and robots using the shared mental model. The scenario we are targeting involves a human worker collaborating with two robotics arms, each having six degrees of freedom, to carry out team missions in the AR environment. The students can learn how to apply social sciences knowledge on robotics systems. We are looking for students who are experience in AR development using Unity, particularly with Magic Leap 2, and proficiency in computer programming languages such as Python, C#, and ROS.
Research Mode: In Lab