I am a Ph.D. candidate in the Computer Science department at the University of Southern California. I work in the Robotic Embedded Systems Lab with Gaurav Sukhatme. I have a Masters degree in CS from USC and I got my B.S. in Engineering from Harvey Mudd College. Before coming to USC I worked as a software engineer for Yahoo! Inc.

I took the photo above on a dark night in Joshua Tree National Park.


You can e-mail me by putting my last name in front of @usc.edu


Rover Path Planning with Value Iteration Networks

Planning for planetary rovers from orbital data is hard. In this project I've developed a new architecture for using value iteration networks to turn the rover path planning problem into an imitation learning problem, where we try to do from orbital data what was previously done from surface imagery, thus enabling path planning at longer ranges and in more places.

Multi-Step Planning

This project looks at solving combined task and motion planning problems using a multi-step planning architecture. We've demonstrated the effectiveness of this approach in simulated and real environments, for problems such as tabletop pick and place, and manipulating an articulated folding chair.

Informative Tactile Sensing

Tactile sensors provide a rich data source for grasping and manipulation problems, but the quality of the data can be influenced in unintuitive ways by choices about how to perform a grasp. This project looked at ways to use machine learning to choose parameters that give us the most useful data.



  • Max Pflueger, Ali Agha, and Gaurav Sukhatme. "Soft Value Iteration Networks for Planetary Rover Path Planning." (Preprint) [PDF]
  • Max Pflueger and Gaurav S. Sukhatme. "Solving Task Space Problems with Multi-Step Planning". (Preprint) [PDF]
  • Max Pflueger and Gaurav S. Sukhatme. "Multi-Step Planning for Robotic Manipulation". Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), May 2015. [PDF] [BibTeX]

Workshop Papers and Posters:


  • "Multi-step Planning for Robotic Manipulation" Presented Febuary 28, 2013 at the USC Computer Science Annual Research Review. [PDF]
  • "Planning for Robotic Manipulation of Articulated Objects" Presented March 8, 2012 at the USC Computer Science Annual Research Review. [PDF]