3D Bevel-Tip Needle Insertion Trajectory Planning via Computational Optimal Control
Manual insertion of flexible bevel-tip needles often leads to unpredictable tissue deformation and compromised targeting accuracy, emphasizing the need for robust trajectory planning. To address this challenge, we formulate the insertion problem as a time-energy optimal control problem (OCP) subject...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11037735/ |
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| Summary: | Manual insertion of flexible bevel-tip needles often leads to unpredictable tissue deformation and compromised targeting accuracy, emphasizing the need for robust trajectory planning. To address this challenge, we formulate the insertion problem as a time-energy optimal control problem (OCP) subject to nonlinear kinematic and collision-avoidance constraints. Due to its large-scale and nonconvex nature, directly solving the nominal OCP is difficult. Instead, we first obtain a coarse collision-free trajectory via <inline-formula> <tex-math notation="LaTeX">${\mathrm {A}}^{\ast }$ </tex-math></inline-formula> search in the abstracted 3D workspace. Next, we create spatiotemporal safe corridors around this trajectory, replace the nominal collision-avoidance constraints with corridor-based constraints, and iteratively relax the kinematic equations as external penalties to refine feasibility. The refined solution subsequently warm-starts a final solve of the nominal OCP with strict kinematic constraints and reduced-scale collision-avoidance constraints. Simulations confirm that our proposed optimization-based trajectory planner converges reliably to numerically optimal needle trajectories, surpassing existing optimization-based trajectory planners in modeling accuracy, solution robustness, and efficiency. |
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| ISSN: | 2169-3536 |