Mentor: Dr. Julie Adams
This project seeks to develop new methods for adapting interaction between a human and a robot in a one-to-one partnership relationship based on the human's cognitive workload. The human dons various wearable sensors that provide a data stream that is analyzed to detect high and low workload conditions. Once a high or low workload condition is detected, the robot can adapt its interaction method with the human. REU students will work to develop new algorithms for detecting changes in workload and new algorithms for adapting the robot's interactive capabilities based on the workload detection. The project will require algorithm design, implementation and software testing. Further, REU students will evaluate the algorithms with actual human-robot teams.
Humans have no trouble picking up and manipulating objects, yet we've struggled to impart that ability to robotic manipulators. This is in part because robotic manipulators lack much of the sensory feedback human hands have, but it's also because we, as humans, are not very good about reasoning about what we do instinctively. The goal of this project is to develop tools and user studies that will let us capture that knowledge and apply it to robotic manipulation tasks.
Design of Implants for Attaching Muscle and Tendons to Improve Human Hand Function
Mentor: Dr. Ravi Balasubramanian
Current reconstructive orthopedic surgeries use sutures to attach muscles and tendons. However, this leads to poor surgical outcomes because of the suture’s limited ability to transmit the muscle’s forces and movement to the tendons. It is expected that using passive implants, such as pulleys and rods, to surgically construct mechanisms in situ using the existing biological tendons will significantly improve post-surgery function (when compared to using sutures) and lead to the development of new surgical procedures.
Example student projects:
As robots become more ubiquitous there are open questions about how we should think of robots in our living spaces. In this project we look specifically at telepresence - "skype on a stick" - where a remote user controls a semi-autonomous robot in your home or office. Unlike a person in your space, we can control what the robot can see, do and hear - for example, blurring or blacking out part of the video to hide what's there, or preventing the robot from going into some rooms.
This project takes a broad look at privacy in the context of remote presence systems, drawing from related work in areas from legal studies to psychology. We are trying to figure out how people think about privacy in the context of these systems, how we can build interfaces that allow people to specify their privacy concerns, and how we can build the underlying technology that supports privacy-protection.
Mentor: Dr. Ross Hatton
Spiders use silk as a tool for moving through space and capturing prey. We're building robots that use these principles to move through complex spaces and lasso targets.
Mentor:Dr. Ross Hatton
Spiders use vibrations in their webs to sense the presence of other insects, similarly to how whales, bats, and submarines use sonar to hunt their prey. In collaboration with a biology team, we're building and instrumenting a giant spider web to examine how this works.
Learning from Humans for Robotic Deburring
Burrs are undesirable projections of material at the edges of a finished part’s surface. They pose a fundamental problem for manufacturing operations since they affect part handling and assembly operations and lead to part failure. Deburring, the process of removing burrs, is currently performed by human operators. But deburring is labor-intensive and causes injury to operators due to the forces and movements involved. This project seeks to learn the deburring process from a human (including forces and movements involved) and develop a robot to automate the deburring process.
Example student projects:
Autonomous Research Vessels to Explore Extreme Ocean Environments
There are many ocean environments which are unsuitable for manned research vessels, either because they are too dangerous (e.g., near a calving glacier or in the deep ocean), or require too many resources to be effective. We seek to design a new generation of Autonomous Research Vessels (ARVs) that can be programmed to measure ocean dynamics in extreme environments. This research project involves the hardware design, construction, and programing of robust surface and underwater systems that will be used to explore ocean dynamics in Greenland, Alaska, and in remote ocean basins. The REU student will join an interdisciplinary team of researchers from mechanical engineering and oceanography to assist in building and programming an ARV currently under construction at Oregon State University.
Autonomous aerial vehicles (e.g., quadcopters) have increased in prominence over the last few years and are seen performing aggressive maneuvers and manipulation tasks on YouTube. These vehicles typically cost upwards of several thousand dollars with a full sensor suite. An open question is the design of a lower-cost vehicle capable of performing autonomous exploration and mapping tasks. This research project involves the development of a team of low-cost rotorcraft capable of fully autonomous exploration and mapping without pre-installed infrastructure. The REU student will primarily assist with implementing the software architecture for the rotorcrafts and testing the flight control, coordination, and mapping accuracy during autonomous operation.
Passive Dynamics and Applied Control for Legged Locomotion
Students on this project will participate in research with our human-scale walking and running robot Cassie. The research requires an interdisciplinary approach combining mechanical design, software, and electronics. Interns may assist with any aspect of this work, focusing on their individual areas of talent, such as mechanical design in SolidWorks, building robot parts, electronics design or wiring, microcontroller software development, Linux-based or Matlab- and Simulink-based software development.
Example Student Projects:
Biologically-inspired Soft Robots
Mentor: Dr. Yigit Menguc
Control of a self-driving wheelchair
Mentors: Dr. Bill Smart
We are working on a self-driving powered wheelchair, for use by people with severe motor disabilities, such as Amyotrophic Lateral Sclerosis (ALS, or Lou Gehrig's disease) and quadriplegia. The goal is to develop a low-cost package that can be added to a traditional powered wheelchair, and turn it into a self-driving system. Self-driving capabilities would afford the wheelchair user more independence, and allow them to move about their world more easily and efficiently.
The project leverages the Robot Operating System (ROS) software for navigation and localization of the system, with special-purpose code for wheelchair-specific features. Our goal is to release both the hardware design and software for the system under an open-source license.Our goal is two-fold: understand how people think about privacy and how that is the same (or different) when it is a robot and not a person, and develop algorithms that lets us "try out" various methods for preserving privacy.
Mentor: Dr. Kagan Tumer
Many interesting real world problems require multiple robots to work together. For example, search and rescue missions require coordinating dozens of autonomous robots, as well as ensuring that the robots and humans work together. But providing hard-coded coordination instructions is too limiting. This project explores the science of coordination, and focuses on how to provide incentives to individual robots so that they work collectively.
Bat Sonar for Robots
Bat sonar is an incredibly rich sense - bats can spot and catch insects in the air, fly through dense forest canopy - all by emitting chirps and listening for echos. They accomplish this feat through deformable ear and nose geometries that let them "shape" the sound scape. In this project we aim to build a soft, deformable bat ear and nose in order to mount such a sensor on the robot.
Robotic Pruning of Fruit Trees
Mentor: Dr. Joe Davidson
The fresh market tree fruit industry is highly labor intensive and is becoming less sustainable with rising costs and shortages of farm labor. Canopy and crop-load management operations, which are essential to improve plant health, control plant size, and increase fruit quality and yield, are highly labor intensive. For example, Washington apple and cherry growers estimate that pruning alone costs about $1,200 - $1,500 per acre per year. Mechanization and automation have the potential to help address these challenges. In this project, we are developing a robotic pruning machine for modern apple orchards.