NRI-CSA stands for National Robotics Initiative - Complementary Situational Awareness for Human-Robot Partnerships.

This is a new 5-year collaborative project involving three collaborative teams at Vanderbilt, Carnegie Mellon, and Johns Hopkins University. The Principal investigators on this grant are Dr. Nabil Simaan (Vanderbilt), Dr. Howie Choset (CMU) and Dr. Russell H. Taylor (JHU).

The grant consists of three partner institutions contributing to laying the foundations to a new concept in robotics that we call Complementary Situational Awareness. Robots have been primarily used to augment human skill during manipulation tasks (e.g. for surgical applications, telemanipulation in hazardous environments) and in some cases to augment sensory presence (e.g. by providing force feedback to surgeons in cases where forces are below humanly perceptible thresholds). In our new approach robots will augment the human user not only in manipulation but also in understanding of the task and in action planning and execution. The idea is that the robots in some cases can sense things beyond human perception and this information may be used by the robot controller to create a model of the environment shape and the interaction characteristics. This robot situational awareness is then used to augment user/surgeon skill and situational awareness for carrying out complex tasks.

Key Project Highlights: Force-controlled Exploration for Updating Virtual Fixtures 

This work deals with development of an approach for using exploration data to update and register an a-priori virtual fixture (high-level assistive telemanipulation law) geometry to a corresponding deformed and displaced physical geometry. This is representative of a robotic surgical intervention where a pre-operative surgical path-plan has to be updated due to organ intra-operative organ shift/swelling. Using hydrid force-motion control, exploration data (position and local surface normal) is used to deform and register the a-priori environment model to the exploration data set. The environment registration is achieved using a deformable registration approach based on coherent point drift. The task-description of the virtual fixture is then deformed and registered in the new environment and the new model is updated and used within a model-mediated telemanipulation framework. The approach is experimentally validated using a da-Vinci research kit (DVRK) master interface and a Cartesian stage robot.

Key Project Highlights: Smultaneous compliance and registration (SCAR) using stiffness and exploration data

Leveraging techniques pioneered by the SLAM community, we present a new filtering approach called simultaneous compliance and registration estimation or CARE. CARE is like SLAM in that it simultaneously determines the pose of a surgical robot while creating a map, but in this case, the map is a compliance map associated with a preoperative model of an organ as opposed to just positional information like landmark locations. The problem assumes that the robot is forcefully contacting and deforming the environment. This palpation has a dual purpose: 1) it provides the necessary geometric information to align or register the robot to a priori models, and 2) with palpation at varying forces, the stiffness/compliance of the environment can be computed. By allowing the robot to palpate its environment with varying forces, we create a force balanced spring model within a Kalman filter framework to estimate both tissue and robot position.

Publications 

  1. E. Ayvali, A. Ansari, L. Wang, N. Simaan and H. Choset, "Utility-Guided Palpation for Locating Tissue Abnormalities," in IEEE Robotics and Automation Letters, vol. 2, no. 2, pp. 864-871, April 2017.

  2. R. A. Srivatsan and Howie Choset, “Multiple Start Branch and Prune Filtering Algorithm for Nonconvex Optimization”, in proceedings of the Workshop on the Algorithmic Fundamentals of Robotics, San Francisco, USA, December 2016.

  3. E. Ayvali, H. Salman, and H. Choset, “Ergodic Coverage In Constrained Environments Using Stochastic Trajectory Optimization”, submitted to the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada, September 24–28, 2017. (In Review)

  4. R. A. Srivatsan, M. Xu, N. Zevallos and H. Choset, “Bingham Distribution-Based Linear Filter for Online Pose Estimation”, the Robotics Science and Systems, 2017.

  5. R. A. Srivatsan, P. Vagdargi and H. Choset, “Sparse Point Registration”, submitted to the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada, September 24–28, 2017. (In Review)

  6. L. Li, B. Yu, C. Yang, P. Vagdargi, R. A. Srivatsan and H. Choset, “Development of an Inexpensive Bi-axial Force Sensor for Minimally Invasive Surgery”, submitted to the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada, September 24–28, 2017. (In Review)

  7. R. A. Srivatsan, P. Vagdargi, N. Zevallos, F. Naina and H. Choset, “Multimodal Approach to Registration Using Stereo Imaging and Contact Sensing”, submitted to RSS workshop, 2017.

  8. R. Roy, L. Wang, and N. Simaan, " Modeling and Estimation of Friction, Extension, and Coupling Effects in Multisegment Continuum Robots," in IEEE/ASME Transactions on Mechatronics, vol. 22, no. 2, pp. 909-920, December 2016.

  9. L. Wang, Z. Chen, P. Chalasani, R. M. Yasin, P. Kazanzides, R.H. Taylor, and N. Simaan, “Force-Controlled Exploration for Updating Virtual Fixture Geometry in Model-Mediated Telemanipulation,” Journal of Mechanisms and Robotics, vol. 9, no.2, pp. 021010, April 2017.

  10. P. Chalasani, R. M. Yasin, L. Wang, N. Simaan, P. Kazanzides and R.H. Taylor, “Constrained Semi-autonomous Telemanipulated Palpation with Assistive Virtual Fixtures,” Hamlyn Symposium on Medical Robotics, London, UK, 2017. (accepted)

  11. Z. Chen, A. Malpani, P. Chalasani, A. Deguet, S. S. Vedula, P. Kazanzides and R. H. Taylor, “Virtual Fixture Assistance for Needle Passing and Knot Tying,” the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Deajeon, South Korea, October 9~14, 2016.

  12. Ayvali, E., Srivatsan, A., Wang, L., Roy, R., Simaan, N. & Choset, H (2016). Using Bayesian Optimization to Guide Probing of a Flexible Environment for Simultaneous Registration and Stiffness Mapping. In International Conference on Robotics and Automation (ICRA’2016), pages 931 - 936.
  13. Bajo, A. & Simaan, N. (2016). Hybrid Motion/Force Control ofMulti-Backbone Continuum Robots. International Journal of Robotics Research, 35(4), 422-434.
  14. Chalasani, P., Wang, L., Roy, R., Simaan, N. & Taylor, R. H (2016). Concurrent Nonparametric Estimation of Organ Geometry and Tissue Stiffness Using Continuous Adaptive Palpation. In International Conference on Robotics and Automation (ICRA’2016), pages 4164-4171.
  15. Roy, R., Wang, L. & Simaan, N (2016b). Investigation of effects of dynamics on intrinsic wrench sensing in continuum robots. In International Conference on Robotics and Automation (ICRA’2016).
  16. Simaan, N., Taylor, R. H. & Choset, H. (2015). Intelligent Surgical Robots with Situational Awareness: from Good to Great Surgeons. ASME Dynamic Systems Magazine(3), 2.
  17. Srivatsan, A. & Choset, H. (2014). Using Lie algebra for shape estimation of medical snake robots. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014), 2014, 3483-3488.
  18. Srivatsan, A. & Choset, H. (2016). Multiple Start Branch and Prune Filtering Algorithm for Nonconvex Optimization. accepted to the Workshop on the Algorithmic Fundamentals of Robotics.
  19. Srivatsan, A., Ayvali, E., Wang, L., Roy, R., Simaan, N. & Choset, H (2016). Complementary model update: A method for simultaneous registration and stiffness mapping in flexible environments. In International Conference on Robotics and Automation (ICRA’2016), pages 924-930.
  20. Srivatsan, A., Rosen, G. T., Ismail, F. N. & Choset, H. (2016). Estimating SE(3) elements using a dual quaternion based linear Kalman filter. Robotics: Science and Systems, July, 2016.
  21. Srivatsan, A., Wang, L., Ayvali, E., Simaan, N. & Choset, H. (2016). Simultaneous Registration and Stiffness mapping of a Flexible Environment using Stiffness and Geometric Prior. The Hamlyn Symposium on Medical Robotics (2016), July, 2016.
  22. Wang, L. & Simaan, N (2014). Investigation of Error Propagation in Multi-Backbone Continuum Robots. In Advances in Robot Kinematics, pages 385-394. Springer International Publishing.
  23. Wang, L., Chen, Z., Chalasani, P., Pile, J., Kazanzides, P., Taylor, R. H. et al (2016a). Updating Virtual Fixtures From Exploration Data in Force-controlled Model-based Telemanipulation. In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (ASME IDETC). Charlotte,NC,USA.