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Post-Doctoral Research

1)  Team MIT: DARPA Robotics Challenge Trials (Finished 4th)

MIT DRC Team's preparation for the DRC Trials (Dec 2013)

Door Task with Sandia Hands

  • M. Fallon, S. Kuindersma, S. Karumanchi,  M. Antone, T. Schneider, H. Dai, C. Perez-D’Arpino, R. Deits, M. DiCicco, D. Fourie, T. Koolen, P. Marion,  M. Posa, A. Valenzuela, P. Kuan-Ting Yu, J. A. Shah, K. Iagnemma, R. Tedrake, S. Teller, "An Architecture for Online Affordance-based Perception and Whole-body Planning", Journal of Field Robotics (JFR) (Special Issue on DARPA Robotics Challenge Trials), 2014.

2) Team MIT: DARPA Virtual Robotics Challenge  (Finished 3rd)

Team MIT's Approach to DARPA Virtual Robotics Challenge

  • R. Tedrake, M. Fallon, S. Karumanchi, S. Kuindersma, M. Antone, T. Schneider, T. Howard, M. Walter, H. Dai, R. Deits, M. Fleder, D. Fourie, R. Hammoud, S. Hemachandra, P. Ilardi, C. Perez-D’Arpino, S. Pillai, A. Valenzuela, C. Cantu, C. Dolan, I. Evans, S. Jorgensen, J. Kristeller, J. A. Shah, K. Iagnemma, S. Teller,  “A Summary of Team MIT’s Approach to the Virtual Robotics Challenge”, IEEE International Conference on Robotics and Automation, 2014. [pdf][watch on youtube]

3)  Mobility Erosion : Guaranteed Motion Safety in environments with hard and soft hazards.

Mobility Erosion Background

I have been developing a min-max morphological operation  that generalizes obstacle growing used in motion planning to soft spaces (space of speed limits). This is termed as Mobility Erosion
  1. Starts with an initial mobility map
  2. Erodes away excess mobility based on estimates of worst case stopping distance.
  3. Eroded mobility map provides speed limits as a function of position  and heading. When adhered to, safety is guaranteed.

Minkowski Sum + Hard Hazards = Safety at low speeds

At high speeds need to take into account the following (in addition to vehicle size and shape):
  • stopping distance
  • latency (actuators and comms)
  • position uncertainty
Mobility Erosion + Hard or Soft Hazards = Safety at high speeds


Sample isotropic and anisotropic erosion among hard hazards

Sample erosion among hard and soft hazards


  • S. Karumanchi, K. Iagnemma, and S. Scheding, “Mobility Erosion: High Speed Motion Safety for Mobile Robots Operating in Off-Road Terrain”, IEEE International Conference on Robotics and Automation, 2013. [pdf]

4) Solving a boundary value problem using a reactive controller.

Mobility Erosion can also be used to create reactive controllers that can generate sub-optimal trajectories to a goal. The controller generalizes to soft hazards and the tuning parameters are environment invariant. 

 Terrain- adaptive local trajectories using forward simulations from a reactive controller

2Comparison to fixed local trajectories.

  • S. Karumanchi and K. Iagnemma , "Reactive control in environments with hard and soft hazards", IEEE Intelligent Robots and Systems, 2012  [pdf].

5)  Operator assist algorithms for tele-operation

          [More details in: MIT news]

MIT & Quantum Signal LLC:: Semi-Autonomous Driving

  • S.J. Anderson, S. Karumanchi , K. Iagnemma,  “Constraint-Based Planning and Control for Safe, Semi-Autonomous Control of Vehicles”, Proceedings of 2012 IEEE Intelligent Vehicles Symposium, June  2012, Alcalá de Henares, Spain. [pdf]