Sarah Tang

Ph.D Candidate, Mechanical Engineering and Applied Mechanics
University of Pennsylvania

I am a second year Ph.D student in Mechanical Engineering at the University of Pennsylvania. I work in the GRASP lab with Dr. Vijay Kumar. My research interests are in robotics (in particular, quadrotors), nonlinear control, hybrid dynamical systems, and multi-robot cooperation. More specifically, I am currently working on aggressive manipulation of cable-suspended payloads with quadrotor systems.

I recieved my B.S.E. degree in Mechanical and Aerospace Engineering from Princeton University in June 2013. My senior thesis was titled "Vision-based control for autonomous quadrotor UAVs" and was advised by Dr. Robert Stengel.

You can find my full CV here.

You can find my Google Scholar profile here.


Conference Publications

Dylan Shinzaki, Chris Gage, Sarah Tang, Mark A. Moline, Barrett Wolfe, Christopher G. Lowe, and Christopher M. Clark. "A multi-auv system for cooperative tracking and following of leopard sharks". In IEEE International Conference on Robotics and Automation (ICRA), 2013. [PDF] [Bibtex]

Ammar Husain, Heather Jones, Balajee Kannan, Uland Wong, Tiago Pimentel, Sarah Tang, Shreyansh Daftry, Steven Huber, and William L. "Red" Whittaker. "Mapping planetary caves with an autonomous, heterogeneous robot team". In IEEE Aerospace Conference, 2013. [PDF] [Bibtex]

Sarah Tang, Dylan Shinzaki, Chris G. Lowe, and Chris M. Clark. "Multi-robot control for circumnavigation of particle distributions". In International Symposium on Distributed Autonomous Robotic Systems (DARS), 2012. [PDF] [Bibtex]

Sarah Tang and Afzal Godil. "An evaluation of local shape descriptors for 3D shape retrieval". In IS&T/SPIE Electronic Imagining, Three-Dimensional Image Processing (3DIP) and Applications II, 2012. [PDF] [Bibtex]


Sarah Tang, Koushil Sreenath, and Vijay Kumar. "Aggressive maneuvering of a quadrotor with a cable-suspended payload". In Robotics: Science and Systems, Workshop on Women in Robotics, 2014.


Graduate Research

Updates to come.

Undergraduate Research

Vision-based formation control for Parrot AR.Drones
Princeton University Senior Thesis

Advisor: Dr. Robert Stengel
Sept. 2012 - June 2013

Abstract: In this work, we propose a vision-based control method for an autonomous team of quadrotor helicopters, or quadcopters. Specifically, we develop three types of control laws that give rise to two behaviors: a Waypoint-Navigation Controller that allows for Trajectory-Following Behavior and two Leader-Follower Controllers that allow for Formation Flight Behavior. We present Matlab simulations to demonstrate the capability of the proposed control design to drive a single UAV to reach desired poses and follow 3D trajectories as well as drive UAV teams to traverse desired paths while maintaining 2D formations. Furthermore, we implement the proposed controllers on a Parrot AR.Drone quadcopter. Experimental results demonstrate the UAV successfully navigating waypoints, following trajectories, and moving into formations with respect to simulated team members.

[Senior Thesis] [Poster]

Autonomous mapping and exploration of planetary caves
Carnegie Mellon University, Robotics Institute Summer Scholars (RISS) Program

Advisor: Dr. William "Red" Whittaker
June 2012 - Aug. 2012

Abstract: Market-based task allocation has proven effective for multi-robot coordination in a number of past works. For such an approach, it is important to have a cost function that accurately represents each robot’s capabilities, which is especially challenging for heterogeneous teams. We propose a generic cost function that aims to learn robot capabilities during execution time for simple and accurate integration into arbitrary multi-robot systems. We implement this cost function on the TraderBots software platform by Carnegie Mellon University and show, through simulation, that the cost function balances task time, quality, workload, and success rate, as indicated by the user. Additionally, we apply it to an exploration mission for a real heterogeneous robotic team to demonstrate its practical usability.

[IEEE Aerospace Conference 2013 Publication, Bibtex] [RISS Program Poster]

Multi-robot control for an autonomous shark-tracking AUV system
Princeton University Junior Independent Work

Advisor: Dr. Christopher M. Clark
Sept. 2011 - June 2012

Abstract: In this work, we present a decentralized controller for the tracking and following of mobile targets, specifically addressing considerations of: 1) not altering target behavior, 2) target states represented by multiple hypotheses, and 3) limited information from bearing-only sensors. The proposed controller drives a team of n robots to circumnavigate an arbitrary distribution of target points at a desired radius from the targets. The controller also dictates robot spacing around their circular trajectory by tracking a desired relative phase angle between neighbors. Simulation results show the functionality of the controller for arbitrary-sized teams and arbitrary stationary and moving particle distributions. Additionally, the controller was implemented on OceanServer Iver2 AUVs. Tracking results demonstrate the controller’s capability to track a desired radius as well as maintain phase with respect to a second AUV.

[ICRA 2013 Publication, Bibtex] [DARS 2012 Publication, Bibtex]

Before Robotics

Evaluation of local shape descriptors for 3D shape retrieval
National Institute of Standards and Technology, Summer Undergraduate Reseach Fellowship

Advisor: Afzal Godil, Dr. Isabel Beichl
June 2011 - Aug. 2011

Abstract: As the usage of 3D models increases, so does the importance of developing accurate 3D shape retrieval algorithms. A common approach is to calculate a shape descriptor for each object, which can then be compared to determine two objects’ similarity. However, these descriptors are often evaluated independently and on different datasets, making them difficult to compare. Using the SHREC 2011 Shape Retrieval Contest of Non-rigid 3D Watertight Meshes dataset, we systematically evaluate a collection of local shape descriptors. We apply each descriptor to the bag-of-words paradigm and assess the effects of varying the dictionary’s size and the number of sample points. In addition, several salient point detection methods are used to choose sample points; these methods are compared to each other and to random selection. Finally, information from two local descriptors is combined in two ways and changes in performance are investigated. This paper presents results of these experiments.

[SPIE 2012 Publication, Bibtex]

A Matlab simulation of speckle calibration for exoplanet detection
Princeton University, Boeing Summer Research Scholarship

Advisor: Dr. N. Jeremy Kasdin, Elizabeth Young
June 2010 - Aug. 2010

Description: A major challenge in the detection of exoplanets is the existence of speckles in the image, which highly resemble that of the planet. A proposed solution is to use the fact that the starlight from which the speckles originate is incoherent with the planet light. Thus, changing the optical layout will cause an interference with the speckles in the image while the planet light remains unchanged, allowing them to be differentiated. In my work this summer, I coded and presented Matlab simulations of two proposed ideas of how to realize this technique.


Snail mail:

Sarah Tang
MEAM University of Pennsylvania
229 Towne Building
220 S. 33rd Street
Philadelphia, PA 19104-6315

Email: sytang[at]seas[dot]upenn[dot]edu