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 general questions or additional information, please contact us using the form below.
May 31, 2020 – August 8, 2020
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.
Haptics for Virtual Reality
This project focuses on the design, building, and control of haptic devices for virtual reality. Current VR systems lack any touch feedback, providing only visual and auditory information to the user. However, touch is a critical component for our interactions with the physical world and with other people. This research will investigate how we use our sense of touch to communicate with the physical world and use this knowledge to design haptic devices and rendering systems that allow users to interact with and communicate through the virtual world. To accomplish this, the project will integrate electronics, mechanical design, programming, and human perception to build and program a device to display artificial touch sensations to a user with the goal of creating a natural and realistic interaction.
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.
Enabling Physical Assistant Robot Autonomy
This project focuses on providing robotic physical assistance to people with disabilities, with an emphasis on the core computational challenges that arise in this domain: what are good models of human behavior, how to learn such models from noisy samples, and how to robustly generate actions for robotic assistants. The research will focus on machine learning algorithms for human behavior modeling, approximation algorithms for robot planning under uncertainty and experimental design of user studies to test the algorithms in deployed robotic systems with actual patients.
Learning Perception and Manipulation for Robots
This project focuses on developing learning-based systems for perception and manipulation for robots. Our emphasis is on the underlying algorithms, with a focus on building experimental systems. The research involves algorithms, software development, system integration, experimentation, and data analysis. In perception we are particularly interested in segmenting, detecting, and identifying objects. For manipulation, we look at how planning techniques, in combination with machine learning, can improve the robot’s manipulation capabilites.
Reward Functions and Deep Reinforcement Learning
This project focuses on the problem of the reward shaping problem in deep reinforcement learning. A fundamental challenge today is that reward functions rely heavily on designer intuition and experience, and as a result tend to be unstructured. The proposal is to use formal specification languages as a means to explore different forms of reward functions. This project will focus on modeling the given robots in a simulation/visualization setup, expressing design requirements in a formal logic such as Signal Temporal Logic, and learning the controller to enforce these requirements while being subject to resource constraints.