Ioan Alexandru Şucan

Past and Current Research Projects

Simultaneous Task and Motion Planning (STAMP)

• In order for robotic devices to perform useful tasks they usually need to execute sequences of motions. I am interested in the simultaneous computation of task plans and motion plans: a discrete sequence of actions and its corresponding continuous motions.
• Relevant Papers:
  • Ioan A. Şucan, Lydia E. Kavraki, Mobile Manipulation: Encoding Motion Planning Options Using Task Motion Multigraphs, IEEE International Conference on Robotics and Automation, 2011. (BibTeX entry).
  • Ioan A. Şucan, Lydia E. Kavraki, On the Advantages of Using Task Motion Multigraphs for Efficient Mobile Manipulation, IEEE International Conference on Intelligent Robots and Systems, 2011. (BibTeX entry).
  • Ioan A. Şucan, Lydia E. Kavraki, Accounting for Uncertainty in Simultaneous Task and Motion Planning Using Task Motion Multigraphs, IEEE International Conference on Robotics and Automation, 2012. (BibTeX entry).

Motion Planning using Real Perception

• In practical applications of motion planning only noisy sensor data is available. I am interested in reducing the gap between perception and planning so that sensed data is more quickly considered in the motion planning process and planning data is used in the perception process.
• Relevant Papers:
  • Ioan A. Şucan, Mrinal Kalakrishnan, Sachin Chitta, Combining Planning Techniques for Manipulation Using Realtime Perception, IEEE International Conference on Robotics and Automation, 2010. (BibTeX entry).
  • Radu B. Rusu, Ioan A. Şucan, Brian P. Gerkey, Sachin Chitta, Michael Beetz, Lydia E. Kavraki, Real-time Perception-Guided Motion Planning for a Personal Robot, IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009. (BibTeX entry).

Motion Planning Under Differential Constraints

• I am interested in the development and application of motion planners that consider the physical properties of robotic devices, and allow fast computation times at the same time.
• Relevant Papers:
  • Ioan A. Şucan, Lydia E. Kavraki, Kinodynamic Motion Planning by Interior-Exterior Cell Exploration, International Workshop on the Algorithmic Foundations of Robotics, 2008. (BibTeX entry).
  • Ioan A. Şucan, Jonathan F. Kruse, Mark Yim, Lydia E. Kavraki, Reconfiguration for modular robots using kinodynamic motion planning, ASME Dynamic Systems and Control Conference, 2008. (BibTeX entry).
  • Ioan A. Şucan, Jonathan F. Kruse, Mark Yim, Lydia E. Kavraki, Kinodynamic Motion Planning with Hardware Demonstrations, IEEE/RSJ International Conference on Intelligent Robots and Systems, 2008. (BibTeX entry).

Estimating Coverage in High-Dimensional State Spaces

• Estimation of coverage while searching high dimensional spaces is a common problem for many sampling-based motion planning algorithms. I am interested in the automatic computation of lower dimensional Euclidean projections that allow estimation of coverage.
• Relevant Papers:
  • Ioan A. Şucan, Lydia E. Kavraki, On the Performance of Random Linear Projections for Sampling-Based Motion Planning, IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009. (BibTeX entry).

Developed Software

• MoveIt!. A framework for motion planning.
• Open Motion Planning Library (OMPL). OMPL consists of a set of sampling-based motion planning algorithms. For more information please see the website of the library.
• Ioan A. Șucan, Mark Moll, Lydia E. Kavraki The Open Motion Planning Library, IEEE Robotics & Automation Magazine, December 2012.

Demo Videos

• Brief presentations of planning with the PR2
  • Demo of OMPL

  • Early demo of replanning

• Motion Planning with Real Perception on a PR2 from Willow Garage. The motion planning code used here is part of the OMPL library, unless otherwise specified.
  • A demo of sampling-based motion planning combined with a trajectory optimization technique (CHOMP) to safely approach and manipulate objects in a replanning context with real-time perception.

  • Manipulation of known grasped objects in a complex environment.

  • Manipulation of known grasped objects in a complex environment.

  • Moving a glass. The task is to move the glass to the right for 30cm without spilling its content.

  • Moving a glass. The task is to move the left-most glass 50cm to the right, without spilling its content.