Robotics and Autonomous Systems (REU)
The Department of Computer Science at University of Southern California offers a 10-week summer research program for undergraduates in Robotics and Autonomous Systems. USC has a large and well established robotics research program that ranges from theoretical to experimental and systems-oriented. USC is a leader in the societally relevant area of robotics for healthcare and at-risk populations (children, the elderly, veterans, etc.); networked robotics for scientific discovery, covering for example environmental monitoring, target tracking, and formation control; using underwater, ground, and aerial robots; and control, machine learning, and perceptual algorithms for grasping, manipulation, and locomotion of humanoid robots. For a comprehensive resource on USC robotics see http://rasc.usc.edu.
Undergraduates in the program will gain research experience spanning the spectrum of cutting edge research topics in robotics. They will also gain exposure to robotics research beyond the scope of the REU site, through seminars by other USC faculty and external site visits, to aid in planning their next career steps. External visits may include trips to the USC Information Sciences Institute (ISI) in Marina del Ray, one of the world’s leading research centers in the fields of computer science and information technology; the USC Institute for Creative Technologies (ICT) in Playa Vista, whose technologies for virtual reality and computer simulation have produced engaging, new, immersive technologies for learning, training, and operational environments; as well as NASA Jet Propulsion Laboratory (JPL) in Pasadena, which has led the world in exploring the solar system’s known planets with robotic spacecraft.
Robotics is an interdisciplinary field, involving expertise in computer science, mechanical engineering, electrical engineering, but also fields outside engineering; this gives the REU students an opportunity to learn about different fields and the broad nature of research. Thus, we welcome applications from students in computer science and all fields of engineering, as well as other fields including neuroscience, psychology, kinesiology, etc. In addition to participating in seminars and social events, students will also prepare a final written report and present their projects to the rest of the institute at the end of the summer.
This Research Experiences for Undergraduates (REU) site is supported by a grant from the National Science Foundation (CNS-1659838).
For questions or additional information, please contact us using the form below.
June 3, 2018 – August 11, 2018
When you apply, we will ask you to rank your top three interests from the research projects listed below. We encourage applicants to explore each mentor’s website to learn more about the individual research activities of each lab.
This project focuses on coordinating teams of robots to autonomously create desired shapes and patterns with minimal user input and minimal communication. Inspired by human abilities to self-localize and self-organize, the research focuses on underlying algorithms for self-localization using information collected by a robots’ onboard sensors. We have run several human studies using an online multi-player interface we developed for our NSF-funded project. Using the interface, participants interact to form shapes in a playing field, communicating only through implicit means provided by the interface. The research involves a combination of designing and testing algorithms for shape formation, coordination, control, and implementation on a testbed of 20 robots specifically designed for this task.
Haptic Feedback for Medical Simulation
Traditionally, haptic feedback for medical simulation and other virtual reality scenarios has focused on creating an approximation of the sensations felt in real-world interactions. However, one of the simulators’ main drawbacks and criticisms is that they do not feel realistic, which is considered by many to hinder widespread adoption of this technology into the medical curriculum. This project will focus on creating realistic haptic feedback for virtual medical simulation using data that is recorded from real-world interactions. We will use tools with attached sensors to measure force, vibration, and position produced during common medical procedures such as inserting a needle, cutting tissue, and suturing. We will then create mathematical models of these signals, which can be used to generate haptic feedback when a user performs virtual procedures in a medical simulator.
Joining USC in Spring 2018
Design and Manufacturing of Biologically Inspired Robots
Taking inspiration from the nature offers new possibilities for realizing novel robots. Biologically-inspired robotics has emerged as an important specialization within the field of robotics. Explorations in this area have included designing and building walking, crawling, and flying robots that mimic kinematics and dynamics of their biological counterparts, understanding and replicating control mechanisms found in biological creatures, and mimicking biological sensing and actuation mechanisms. This project focuses on designing and fabricating biologically inspired robots. The main emphasis is on identifying the general principles behind taking inspiration from a biological source and converting the inspiration into implementable engineering concepts that can be incorporated into a robot. Realizing a biologically-inspired robot often requires utilizing advanced manufacturing processes for realizing complexity observed in biological creatures. Therefore, this project leverages recent advances in manufacturing to realize biologically inspired robots.
Robotic Wireless Sensing and Communication Networks
The research projects at the Autonomous Networks Research Group will focus on the design and evaluation of networks of robotic nodes for sensing and communication applications. The research spans the design and analysis of algorithms, mathematical modeling, software implementation and evaluation via simulations and testbeds. The mathematical modeling and algorithm design approaches draw from a broad range of tools including stochastic optimization and control, game theory, machine learning, including reinforcement learning and classification, estimation theory, etc.
Socially Assistive Robotics
This project focuses on socially assistive robotics, developing systems capable of aiding people through social interactions that combine monitoring, coaching, motivation, and companionship. The research focuses on the development of human-robot interaction algorithms (involving control and learning in complex, dynamic, and uncertain environments by integrating on-line perception, representation, and interaction with people) and software for providing personalized assistance in convalescence, rehabilitation, training, and education. The research involves a combination of algorithms and software, system integration, and human subjects evaluation studies design, execution, and data analysis. To address the inherently multidisciplinary challenges of this research, the work draws on theories, models, and collaborations from neuroscience, cognitive science, social science, health sciences, and education.
Agile Small-Form-Factor Software-Defined Radars for UAVs
We often build remote sensing systems such as radars that are large, bulky, and expensive systems, for collecting data about environmental variables such as water content in soil, crop growth, deforestation and regrowth, wildfires, etc. These “cadillac” versions of instruments are usually developed over many months or even years, and fly on large airborne or space borne platforms. They require the involvement of large companies and government agencies that operate such platforms. A more recent and complementary approach that is gaining a lot of attention is to build much smaller (even if less fancy or capable) versions of these sensors and install them on small uninhabited aerial vehicles (UAVs), which can be deployed more easily, faster, and at much lower costs, and therefore make them more widely available. We can then also develop groups of such systems and fly them as a network and in formation. Several REU projects can be defined for designing, building, integrating, and testing these instruments. Project can include hardware and software aspects for various subsystems and their integration into the overall system.
Projects under this topic emphasize the need for a tight coordination of perception, action, and learning, rather than the classical view that perception, action, and learning can be addressed as isolated topics. These issues can be investigated in the context of perception for action, manipulation, locomotion, or simply whole-body coordination. Research in such areas requires a rather multidisciplinary knowledge, including machine learning, robot control, 3D perception for robotics, and experimental robotics, including software engineering and real-time control. Our experimental platforms include small scale humanoid robots (NAOs), two full body humanoid robots, robot arms with perception systems, and various reduced robot systems like arms, hands, and vision heads.
Autonomy for Aquatic Robots
This project focuses on developing networked multi-robot systems capable of communicating among themselves and unattended, immobile, wireless sensors. Our emphasis is on the underlying algorithms for coordination and control, with a focus on building useful fielded systems. In collaboration with a team of marine biologists we are working on developing and testing robotic systems for aquatic monitoring, both as tools for scientific discovery, and systems for environmental monitoring and stewardship. The research involves algorithms, software development, system integration, field-testing, and data analysis.