Efficient Smoothing of Piecewise Linear Paths with Minimal Deviation

Waringo, Michel; Henrich, Dominik

doi:10.1109/iros.2006.281795

Cited by 10 publications

(4 citation statements)

References 8 publications

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“…In [61], one of such algorithms is presented and applied on any given path. The algorithm limits the allowable deviation from the original path and results in a new path with fewer nodes.…”

Section: Literature Reviewmentioning

confidence: 99%

Sampling-Based Motion Planning Algorithms for Replanning and Spatial Load Balancing

Boardman¹

2017

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“…In [61], one of such algorithms is presented and applied on any given path. The algorithm limits the allowable deviation from the original path and results in a new path with fewer nodes.…”

Section: Literature Reviewmentioning

confidence: 99%

Sampling-Based Motion Planning Algorithms for Replanning and Spatial Load Balancing

Boardman¹

2017

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“…In this section, we consider only paths with positional coordinates and no orientation and we do not use any constraints Henrich D., 2006). Depending on the application, different error functions K can be used.…”

Section: Path Deviation Functions For a Fixed Orientationmentioning

confidence: 99%

Smoothing of Piecewise Linear Paths

Waringo¹,

Henrich²

2008

Motion Planning

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“…In order to allow faster and less jerky scanning, the scan path P is smoothed by successively removing points until the resulting path deviation exceeds an application-specific threshold [16]. In the following, the smoothing procedure we developed is explained.…”

Section: B Scan Path Smoothingmentioning

confidence: 99%

“…The algorithm for removing path points is described in detail in [16]. Figure 6 shows an initial US scan path and the result of path smoothing using error function K1 and a maximum deviation of I.Omm.…”

Section: B Scan Path Smoothingmentioning

confidence: 99%

Robot-Based 3D Ultrasound Scanning and Registration with Infrared Navigation Support

Stolka

Waringo

Henrich

et al. 2007

Proceedings 2007 IEEE International Conference on Robotics and Automation

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Surgical procedures with navigation or robot system support usually require pre-operative planning data. This data can be acquired with imaging techniques such as computed tomography (CT), the current gold standard due to its high precision. With such imaging data, access trajectories, implant positions, individual milling paths etc. can be computed. We present a novel ultrasound-based method to generate 3D image data which is well-suited for many interventions, but less costly than equivalent CT data. The method's feasibility is demonstrated for robot-based implant bed milling in the lateral skull base, in a process consisting of infrared navigation registration, manual ultrasound scan path delineation, path smoothing and checking, and robot-based ultrasound scan execution.

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Efficient Smoothing of Piecewise Linear Paths with Minimal Deviation

Cited by 10 publications

References 8 publications

Sampling-Based Motion Planning Algorithms for Replanning and Spatial Load Balancing

Sampling-Based Motion Planning Algorithms for Replanning and Spatial Load Balancing

Smoothing of Piecewise Linear Paths

Robot-Based 3D Ultrasound Scanning and Registration with Infrared Navigation Support

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