James Alan Preiss

I am a Ph.D. student at the USC Robotic Embedded Systems Lab in Los Angeles, CA, advised by Prof. Gaurav Sukhatme. In summer of 2019, I will join Google NYC as a research intern.

I am interested in understanding the structure of optimization problems encountered in robotics and machine learning. My past projects include algorithms and hardness results in trajectory optimization for state observability, and multi-robot motion planning using a discrete/continuous decomposition. I currently focus on reinforcement learning in continuous spaces, particularly on how the system dynamics affect the difficulty of learning.

I also helped design and build USC's Crazyswarm 49-quadcopter research facility. Before joining RESL, I worked as a professional software developer on industrial 3d scanning tools at Geomagic and the JMP visual statistics package at SAS. I completed a B.S. in Mathematics and B.A. in Photography at The Evergreen State College in Olympia, WA.

This page last updated March 2019.

• Trajectory Planning for Quadrotor Swarms
• Downwash-Aware Trajectory Planning for Large Quadcopter Teams
• Crazyswarm: A Large Nano-Quadcopter Swarm
• Observability-Aware Trajectory Optimization for Self-Calibration with Application to UAVs

• Understanding the Variance of Policy Gradient Estimators in Reinforcement Learning.
  Sébastien M. R. Arnold, James A. Preiss, Chen-Yu Wei and Marius Kloft.
  Southern Californial Machine Learning Symposium (2019). [preprint: coming soon!] Awarded best poster
• Learning a System-ID Embedding Space for Domain Specialization with Deep Reinforcement Learning.
  James A. Preiss, Karol Hausman, Gaurav S. Sukhatme.
  NeurIPS 2018 Workshop on Reinforcement Learning under Partial Observability. [pdf]
• Simultaneous Self-Calibration and Navigation using Trajectory Optimization.
  James A. Preiss, Karol Hausman, Gaurav S. Sukhatme, and Stephan Weiss.
  International Journal of Robotics Research (IJRR), Invitation-only RSS 2017 special issue. [official page] [preprint]
• Trajectory Planning for Quadrotor Swarms.
  Wolfgang Hönig, James A. Preiss, T.K. Satish Kumar, Gaurav S. Sukhatme, and Nora Ayanian.
  IEEE Transactions on Robotics (T-RO), special issue on aerial swarm robotics. [preprint] [video]
• Trajectory Optimization for Self-Calibration and Navigation.
  James A. Preiss, Karol Hausman, Gaurav S. Sukhatme, and Stephan Weiss.
  Robotics: Science and Systems (RSS), 2017. [pdf]
• Downwash-Aware Trajectory Planning for Large Quadcopter Teams.
  James A. Preiss, Wolfgang Hönig, Nora Ayanian, and Gaurav S. Sukhatme
  IEEE International Conference on Intelligent Robots and Systems (IROS), 2017. [arXiv version] [video]
• Crazyswarm: A Large Nano-Quadcopter Swarm.
  James A. Preiss, Wolfgang Hönig, Gaurav S. Sukhatme, and Nora Ayanian.
  IEEE International Conference on Robotics and Automation (ICRA), 2017. [pdf] [video]
• Observability-Aware Trajectory Optimization for Self-Calibration with Application to UAVs.
  Karol Hausman, James A. Preiss, Gaurav S. Sukhatme, and Stephan Weiss.
  IEEE Robotics and Automation Letters (RA-L), 2017. [arXiv version] [video]

• crazyswarm - our full stack for flying 49+ Crazyflie quadcopters in a motion capture space. Includes object tracking, improved radio protocols, onboard sensor fusion, nonlinear controller, onboard trajectory planning, ROS node, and Python scripting.
• smoothener - convert multi-robot waypoint sequences into smooth piecewise polynomial trajectories. Implementation of the continuous portion of our IROS 2017 paper.
• cmath3d - a 3d math library for embedded C
• pputils - utilities for working with piecewise polynomials in Matlab's ppform.
• quatcompress - compress a quaternion into 32 bits

(first initial) (middle initial) (last name) @ usc.edu