Planning curvature-constrained paths to multiple goals using circle sampling

Edgar Lobaton, Jinghe Zhang, Sachin Patil, Ron Alterovitz
2011 2011 IEEE International Conference on Robotics and Automation  
We present a new sampling-based method for planning optimal, collision-free, curvature-constrained paths for nonholonomic robots to visit multiple goals in any order. Rather than sampling configurations as in standard samplingbased planners, we construct a roadmap by sampling circles of constant curvature and then generating feasible transitions between the sampled circles. We provide a closed-form formula for connecting the sampled circles in 2D and generalize the approach to 3D workspaces. We
more » ... then formulate the multigoal planning problem as finding a minimum directed Steiner tree over the roadmap. Since optimally solving the multi-goal planning problem requires exponential time, we propose greedy heuristics to efficiently compute a path that visits multiple goals. We apply the planner in the context of medical needle steering where the needle tip must reach multiple goals in soft tissue, a common requirement for clinical procedures such as biopsies, drug delivery, and brachytherapy cancer treatment. We demonstrate that our multi-goal planner significantly decreases tissue that must be cut when compared to sequential execution of single-goal plans.
doi:10.1109/icra.2011.5980446 pmid:22294101 pmcid:PMC3268135 dblp:conf/icra/LobatonZPA11 fatcat:y6wkm4vo2bguxk6q25a5izsuri