Planning fireworks trajectories for steerable medical needles to reduce patient trauma

  • Authors:

  • Jijie Xu;Vincent Duindam;Ron Alterovitz;Jean Pouliot;J. Adam M. Cunha;I-Chow Hsu;Ken Goldberg

  • Affiliations:

  • B. Thomas Golisano College of Computing and Information Science, Rochester Institute of Technology;Department of Electrical Engineering and Computer Sciences, University of California, Berkeley;Department of Computer Science, University of North Carolina at Chapel Hill;Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco;Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco;Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco;Department of Industrial Engineering and Operations Research and the Department of Electrical Engineering and Computer Sciences, University of California, Berkeley

  • Venue:
  • IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
  • Year:
  • 2009

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Abstract

Accurate insertion of needles to targets in 3D anatomy is required for numerous medical procedures. To reduce patient trauma, a "fireworks" needle insertion approach can be used in which multiple needles are inserted from a single small region on the patient's skin to multiple targets in the tissue. In this paper, we explore motion planning for "fireworks" needle insertion in 3D environments by developing an algorithm based on Rapidly-exploring Random Trees (RRTs). Given a set of targets, we propose an algorithm to quickly explore the configuration space by building a forest of RRTs and to find feasible plans for multiple steerable needles from a single entry region. We present two path selection algorithms with different optimality considerations to optimize the final plan among all feasible outputs. Finally, we demonstrate the performance of the proposed algorithm with a simulation based on a prostate cancer treatment environment.