PhD Candidate in Mechanical Engineering & Applied Mechanics

University of Pennsylvania, GRASP Lab

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I am currently a PhD student in Mechanical Engineering and Applied Mechanics at the University of Pennsylvania, working in the General Robotics, Automation, Sensing & Perception (GRASP) Lab with Dr. Vijay Kumar.

My research interests are in developing planning and control algorithms that allow robots to 1. execute aggressive, acrobatic maneuvers to complete tasks more efficiently or complete otherwise infeasible tasks and 2. reason about their dynamic and sensor capabilities to decide how aggressively or conservatively to behave to maintain minimum safety guarantees. I am particularly interested in finding techniques that allow teams of robots to work together a manner that minimally compromises indiviudal robots' agilities.

Currently, I am focused on developing mechanisms for suspended payload manipulation with aerial robots. While previous works always constrain the payload to be swing-free, our methods allow for the incorporatation of large, yet controlled, load swings for faster, more energy-efficient transport. This mode of operation closely mimics the behavior of expert pilots in tasks such as aerial fire-fighting, load transportation, construction, heli-mulching, crop seeding, logging, and tree harvesting. My work spans three intersecting themes: generation of aggressive, but safe payload trajectories in cluttered environments (PLANNING), scalable coordination of robot teams (COORDINATION), and interfacing of planning and geometric control techniques with onboard estimation and perception (SENSING).

Besides quadrotors, I am excited about robots of all shapes and sizes. I have also worked on self-driving cars at Google, mobile robots for cooperative mapping at the Carnegie Mellon University Robotics Institute, underwater robots for autonomous shark tracking at Princeton, and shape descriptors for classification of 3D meshes at NIST.

MIQP trajectory planning for quadrotors with cable-suspended payloads

In this work, we propose an optimization-based trajectory planning algorithm that allows for incorporation of large, yet controlled, payload swings when appropriate. We demonstrate two novel capabilities: maneuvering through difficult obstacles, such as windows whose height is smaller than the cable length, and rapid payload pick-up and releases without the quadrotor moving directly above the payload. This is the first experimental demonstration of these types of maneuvers, which could enable automate rapid Christmas tree harvesting and delivery to hard-to-access disaster sites.

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Sarah Tang and Vijay Kumar. “Mixed integer quadratic program trajectory generation for a quadrotor with a cable-suspended payload”. IEEE International Conference on Robotics and Automation (ICRA). Seattle, WA. May 2015.

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Sarah Tang and Vijay Kumar. “Planning aggressive maneuvers for a quadrotor with a cable-suspended payload.” IEEE International Conference on Robotics and Automation (ICRA), Becoming a Robot Guru: Integrating Science, Engineering, and Creativity Workshop. Seattle, WA. May 30, 2015. Poster presentation.

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Sarah Tang, Koushil Sreenath, and Vijay Kumar. “Aggressive maneuvering of a quadrotor with a cable-suspended payload”. Robotics: Science and Systems (RSS), Workshop on Women in Robotics. Berkeley, CA. July 12, 2014. Poster presentation.

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Sarah Tang. “Aggressive maneuvering of a quadrotor with a cable-suspended payload". University of Pennsylvania Qualification Report, 2014.

Vision-based geometric control of suspended payloads

Geometric controllers can theortically guarantee stable control of the quadrotor-with-suspended-payload system through configurations where the payload is swung far from the vertical. However, this control approach has not yet been realized in practice. In this work, by using data from a downward facing camera and an onboard IMU, we are able to accurately estimate the payload state and utilize a geometric controller to robustly control agile maneuvers that include payload swings of up to 50 degrees from the vertical. This is the first experimental demonstration of closed-loop feedback control in the three-dimensional workspace for this system and represents a step towards automated payload maneuvering in real-world applications.

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Sarah Tang*, Valentin Wüest*, and Vijay Kumar. (*Equal contribution.) “Aggressive flight with suspended payloads using vision-based control”. Robotics and Automation Letters (RA-L). To be presented at IEEE International COnference on Robotics and Automation (ICRA) 2018. In press.

Automated payload delivery with quadrotor teams

Most multi-robot systems currently used consist of approximately first- or second-order vehicles. Instead, we consider a team of quadrotors, each carrying a cable-suspended payload, and develop an algorithm for safe simultaneous navigation of all payloads to designated goal positions. We do not constrain the payloads to remain vertical, but instead, allow them to swing upwards when it is safe to do so. This work is the first demonstration of a multi-robot team with vehicles of this level of complexity and is applicable to tasks such as construction, where a single crane performing sequential tasks can be replaced by multiple quadrotors.

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Sarah Tang, Koushil Sreenath, and Vijay Kumar. "Multi-robot trajectory generation for an aerial payload delivery system". In International Symposium on Robotics Research (ISRR). Puerto Varas, Chile. Dec. 2017.

Scalable multi-robot trajectory generation with QPs

Trajectory planning for multi-robot teams is a difficult problem --- the problem's search space grows exponentially with the number of robots and each robot often contains kinemtic or dynamic constraints that its trajectory must satisfy. In this light, we propose a two-step algorithm for multi-robot planning. First, a fast (though sub-optimal) motion planning algorithm designs local roundabout-like collision avoidance maneuvers to navigate all robots safely to designated goal positions. Then, a trajectory smoothing process generates a safe, dynamically feasible trajectory for each robot. Unlike past works that optimize all robots’ trajectories in a single optimization problem, our algorithm constructs an independent optimization problem for each vehicle, giving it polynomial, instead of exponential, computation time complexity with respect to the number of robots. We show that this method can safely navigate quadrotors in close proximities.

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Sarah Tang, Justin Thomas, and Vijay Kumar. “Hold or take optimal plan (HOOP): a quadratic programming approach to multi-robot trajectory generation”. International Journal of Robotics Research (IJRR). In press.

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Sarah Tang, Justin Thomas, and Vijay Kumar. “Safe navigation of quadrotor teams to labeled goals in limited workspaces”. International Symposium on Experimental Robotics (ISER). Tokyo, Japan. Oct. 2016.

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Sarah Tang and Vijay Kumar. “Safe and complete trajectory generation for robot teams with higher-order dynamics”. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Daejeon, Korea. Oct. 2016.

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Sarah Tang and Vijay Kumar. “A complete algorithm for generating safe trajectories for multi-robot teams". International Symposium on Robotics Research (ISRR). Sestri Levante, Italy. Sept. 2015.

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Sarah Tang and Vijay Kumar. “Translating paths into optimal trajectories for safe coordination of teams of dynamic robots.” Robotics: Science and Systems (RSS), Workshop on On-line Decision-Making in Multi-robot Coordination. Ann Arbor, Michigan. June 19, 2016. Oral presentation.

Real-time planning with an onboard RGB-D sensor

Bringing robots out of motion-capture arenas and into real-world environments is a challenging task that requires interfacing planning algorithms with onboard perception and mapping algorithms. In this work, we propose a method for finding safe, dynamically feasible trajectories through an occupancy grid map built using an onboard RGB-D sensor and demonstrate the execution of the complete obstacle detection to mapping to trajectory execution pipeline on a quadrotor.

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Sikang Liu, Michael Watterson, Sarah Tang, and Vijay Kumar. “High speed navigation for quadrotors with limited onboard sensing”. IEEE International Conference on Robotics and Automation (ICRA). Stockholm, Sweden. May 2016.

Market-based task allocation for cooperative mapping with heterogenous ground robots

Deploying robots into unknown regions to create maps is a common application for ground robots. Using a heterogenous team for this task allows for mapping across different types of terrains and data collection from different sensors. In this work, we describe a framework for autonomous exploration using such a team and demonstrate its usage in modeling a rugged tunnel enviornment.

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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". IEEE Aerospace Conference. Big Sky, MT. Mar. 2013.

Decentralized control for shark tracking with a team of autonomous underwater robots

Collecting data on the behavior of long migratory fish species is crucial to the field of marine biology. Unfortunately, current methods for fish tracking suffer significant drawbacks. Satellite tags are able to track fish across long distances, however, can only gather measurements when the fish are at the water’s surface. Acoustic tags are able to function underwater, but require researchers to manually track and follow the fish on boats, which is labor intensive and unsustainable over large distances. Autonomous Underwater Vehicles (AUVs) could potentially solve both these challenges. They can be equipped with acoustic receivers for accurate tracking and have long battery lives for continuous data collection. In this work, we develop a control mechanism that allows a team of AUVs to follow and track a leopard shark.

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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". IEEE International Conference on Robotics and Automation (ICRA). Karlsruhe, Germany. May 2013.

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Sarah Tang, Dylan Shinzaki, Chris G. Lowe, and Chris M. Clark. “Multi-robot control for circumnavigation of particle distributions". International Symposium on Distributed Autonomous Robotic Systems (DARS). Baltimore, MD. Nov. 2012.

Benchmarking 3D descriptors for shape retrieval

3D shape retrieval is the process of identifying the subset of 3D models in a collection that are the same as a given query. This problem is challenging, as models can be in different poses or represented from different viewing angles. Many works have focused on developing shape descriptors, scalar or vector quantities calculated at chosen points on the meshes, to determine two models’ similarity. However, proposed descriptors are often evaluated independently and on different datasets. This paper systematically compares a number of prominent 3D shape descriptors and benchmarks their performance.

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

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Sarah Tang. “An evaluation of local shape descriptors for 3D shape retrieval". NIST Interagency/Internal Report (NISTIR) 7812. Mar. 2012.

Research talks at Google Brain and Nvidia

Thank you to Google and Nvidia for allowing me to share my research, "Dynamic manipulation with aerial robot teams"!

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“Dynamic manipulation with aerial robot teams". Google Brain. Mountain View, CA, Feb. 28, 2018. Nvidia. Seattle, WA, March 1, 2018.

University of Pennsylvania iTalks

In 2015, I participated in Penn’s iTalks competition, an event where participants gave 12-minute TED-talk style presentations that were judged by a faculty panel and the student audience on clarity of presentation, impact of work, and interdisciplinary nature of research. This talk won the Best Presentation (determined by faculty judges) and the Audience Favorite (determined by audience voting) Awards.

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“Planning for aggressive maneuvers for a quadrotor with a cable-suspended load". Interdisciplinary Talks (iTalks) Competition".University of Pennsylvania. Philadelphia, PA. Apr. 1, 2015.

Princeton University Center for Information Technology Policy panel

"This talk is the second in our “Can Law Keep Up with New Technology?” series of lunch timers. Each program explores the current state of an emerging technology and the legal and ethical considerations that stem from it. Peter Asaro and Sarah Tang will discuss non-military drones: what is possible now and in the near future using drone technology and how we should think about their effect on privacy in public space, considering surveillance and remote sensing capabilities."

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“Lunch Timer with Peter Asaro and Sarah Tang – Non-Military Drones: What Laws and Ethics Do We Need?"Princeton University, Center for Information Technology Policy. Princeton, NJ. Mar. 30, 2015.

Tutorial talk at the Technology Management Conference at Saab Dynamics

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“Quadrotor swarms: hardware, algorithms, and applications". Annual Technology Management Conference at Saab Dynamics. With Philip Dames. Karlskoga, Sweden, Feb. 4, 2015. Linköping, Sweden, Feb. 5, 2015.

Drones learn tricks with suspended loads, through-window package delivery inevitable

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"Drones learn tricks with suspended loads, through-window package delivery inevitable". IEEE Spectrum. Oct. 13, 2014.

Penn’s GRASP Lab receives $5.5 million for ‘fast, light and autonomous’ flying robots

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"Penn’s GRASP Lab receives $5.5 million for ‘fast, light and autonomous’ flying robots". Penn News. Nov. 3, 2015.

Survey of advancements towards fast flight on quadrotors

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“Autonomous flying”, in: Annual Reviews in Control, Robotics, and Autonomous Systems, 1st ed, vol. 1. N. Leonard, Ed. California: Annual Reviews, 2018. In press.

Survey of networked robotics

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“Networked robotics”, in: Encyclopedia of Robotics, 1st ed, M. H. Ang, Ed. Berlin Heidelberg: Springer-Verlag, 2019. In press.

Aerial Robotics Coursera course

Our Coursera course on Aerial Robotics, part of a 5-course series on Robotics from the Penn GRASP Lab, is now live!

coursera aerial robotics

GRASP Research Experience for Undergraduates

During the summer of 2014, I worked with an incredible REU student on a research project titled “Autonomous Flight and Landing of a Quadrotor on a Moving Ground Vehicle Using April Tag Vision-Based Control”, which won the Best Presentation Award!

Autonomous Flight and Landing of a Quadrotor by Sarah Cen

Army Educational Outreach Program, Research & Engineering Apprenticeship Program

During the summer of 2017, I served as a mentor for the Army Educational Outreach Program, Research & Engineering Apprenticeship Program. I worked with a high school student to quantify and analyze inter-robot aerodynamic effects in a team of bitcraze Crazyflie robots during formation flight.

team of crazyflie quadrotors

USA Science and Engineering Festival

In April 2016, the GRASP lab hosted a booth at the USA Science and Engineering Festival, featuring our running, hopping, rolling, and flying robots!

GRASP lab robot

FIRST Lego League

From 2014–2016, I was honored to volunteer as a judge for the FIRST Lego League Championships at Penn!

lego robot

Rube Goldberg Celebration

From 2011–2012, I served as the Science Programming Assistant for the Cotsen Children’s Library at Princeton University, where I helped organize and facilitate events at the intersection of science and literature. One of our most successful initiatives was the first Rube Goldberg celebration, which featured this book-turning Rube Goldberg Machine (constructed with Tanner DeVoe).

Princeton Engineering Education for Kids (PEEK)

I was involved in Princeton Engineering Education for Kids (PEEK) from 2009–2013 as a volunteer and 2010–2012 as co-project coordinator. Our flagship initiative was a five-lesson series with every third grade classroom in the Princeton Regional School District. We also worked with a middle school engineering club, the Princeton Public Library, and presented at one-time outreach events throughout the school year.

Robot made by kids

Profile photo of Sarah Y Tang


PhD Candidate. University of Pennsylvania, Mechanical Engineering & Applied Mechanics. In progress. Advised by Dr. Vijay Kumar.

MSE. University of Pennsylvania, General Robotics, Automation, Sensing & Perception (GRASP) Laboratory, Robotics. Dec. 2015.

BSE. Princeton University, Mechanical & Aerospace Engineering. Jun. 2013. Advised by Dr. Robert Stengel and Dr. Christopher M. Clark.


Google Self-Driving Car. Software Engineering Intern. Summer 2016.

Carnegie Mellon University Robotics Institute. Research Intern. Summer 2012.

National Institute of Standards and Technology. Research Intern. Summer 2011.



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CURRICULUM VITAE. Updated Jan. 16, 2018.