An Orbital Velocity-Based Obstacle Avoidance Algorithm for Surgical Robots

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 194)

Abstract

This paper introduces an obstacle avoidance methodology of autonomous assistant robot for surgery. Currently employed master-slave surgical robots just copy movements that a surgeon creates. This kind of behavior causes unexpected collision on a vulnerable surface of an organ and makes possibility of danger which causes serious injury. Many of diagnostic technology with navigation systems are used to make up for these disadvantages and an obstacle avoidance algorithm in this research also contribute to raise safety of surgery. We present 4 states of two instruments in terms of shortest distance as a measure of collision. Then, the autonomous motion of a robotic instrument is generated by a motion planning algorithm which incorporates an orbital velocity component into attractive potential function. As a result, the robotic instrument exhibits a natural maneuver movement around obstacles. A hardware-in the-loop approach is employed to control the motion of the two instruments and the effectiveness of the proposed motion planning algorithm was verified through several simulation examples.

Keywords

Obstacle Avoidance Autonomous movement Trajectory planning Medical robot 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Niemeyer, G., Swarup, N., Guthanrt, G., Toth, G., Younge, R., Nowlin, W.: Camera Referenced Control in a Minimally Invasive Surgical Apparatus. World patent WO0060521Google Scholar
  2. 2.
    Inoue, S., Toyoda, K., Kobayashi, Y., Fujie, M.G.: Autonomous Avoidance based on Motion Delay of Master-Slave Surgical Robot. In: International Conference of the IEEE EMBS (September 2009)Google Scholar
  3. 3.
    Kang, H., Wen, J.T.: Robotic Assistants aid Surgeons During Minimally Invasive Procedures. IEEE Engineering in Medicine and Biology Magazine 20(1) (2001)Google Scholar
  4. 4.
    Dumpert, J., Lehman, A.C., Wood, N.A., Oleyniko, D., Farritor, S.M.: Semi-Autonomous Surgical Tasks Using a Miniature in Vivo Surgical Robot. In: Proc. of IEEE Int. Conf. on Engineering in Medicine and Biology Society, EMBC (2009)Google Scholar
  5. 5.
    Khatib, O.: Real-time Obstacle Avoidance for Manipulators and Mobile Robots. In: Proc. of IEEE Int. Conf. on Robotics and Automation, pp. 500–505 (1985)Google Scholar
  6. 6.
    Brock, O., Khatib, O.: Real-Time Replanning in High-Dimensional Configuration Spaces Using Sets of Homotopic Paths. In: Proc. of Int. Conf. on Robotics and Automation, pp. 550–555 (2000)Google Scholar
  7. 7.
    Cen, Y., Wang, L., Zhang, H.: Real-time Obstacle Avoidance Strategy for Mobile Robot Based On Improved Coordinating Potential Field with Genetic Algorithm. In: Proc. of IEEE Int. Conf. on Control Applications, pp. 415–419 (2007)Google Scholar
  8. 8.
    Chancharoen, R., Sangveraphunsiri, V., Sanguanpiyapan, K., Chatchaisucha, P., Dharachantra, P., Nattarorn, S., Pongparit, S.: Collision Avoidance Technique for Uncalibrated Visual Servoing for Industrial Robots. In: Proc. of IEEE Int. Conf. on Industrial Technology, pp. 594–599 (2002)Google Scholar
  9. 9.
    Kumar, R., Jensen, P., Taylor, R.: Experiments with a Steady Hand Robot in Constrained Compliant Motion and Path Following. In: Proc. of IEEE International Workshop on Robot and Human Interaction (1999)Google Scholar
  10. 10.
    Iraji, R., Manzuri-Shalmanit, M.T.: A New Fuzzy-Based Spatial Modelfor Robot Navigation among Dynamic Obstacles. In: Proc. of IEEE International Conference on Control and Automation (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Electronic Systems EngineeringHanyang UniversityAnsanKorea

Personalised recommendations