MSISpIC: a probabilistic scan matching algorithm using a mechanical scanned imaging sonar

Bes, Emili Hernàndez; Rodríguez, Pere Ridao; Romagós, David Ribas; Grabulosa, Joan Batlle i

doi:10.14198/jopha.2009.3.1.02

Cited by 31 publications

(35 citation statements)

References 16 publications

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“…Many works have pointed to effective variants based on the ICP framework in order to improve the rate of convergence, such as the mechanical scanning imaging sonar probabilistic iterative correspondence method (MSISpIC) [29], metric-based iterative closest point method (mbICP) [42], and other high-speed variants [25], which should be integrated into a more comprehensive implementation of the navigation architecture. Given that many inertial measurement units can still maintain centimeter resolution over the course of a few seconds [58], the results from using the ICP method should not be hindered from limiting factor is then defined by the noise contributed by both the original 3D sonar reference map and the real-time sonar scans of the decommissioning vehicle.…”

Section: Distance Minimizationmentioning

confidence: 99%

Navigation and manipulation for autonomous underwater dismantling of offshore structures

Welch¹

2015

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The dismantling of offshore structures, known as decommissioning, is a complex task in the oil and gas industry, driven by strict environmental standards. As the environments in which decommissioning is necessary become more challenging, autonomy presents itself as a solution to conduct this work as cost-effectively and safely as possible, namely by taking Remotely Operated Vehicles (ROVs) and divers out of the equation. In this thesis, three avenues are researched in support of Autonomous Underwater Vehicles (AUVs) for decommissioning: navigation, attachment, and manipulation. First, the Iterative Closest Point method (ICP) is investigated as a means to correct position drift of an inertial navigation system, by using a previously obtained coarse map. Using real sonar data from a current decommissioning site in the Gulf of Mexico, the algorithm is able to reconcile the internally dead-reckoned pose of the vehicle with that calculated via ICP, to an accuracy of 7cm from a 100k-point sonar scan. Second, to attach lifting points to subsea scrap without bracing onto it, a single mechanism was designed to both drill and affix anchors in a single penetration, from a vehicle in free flight. A prototype was fabricated and its functionality verified. Third, to promote robust and stable robotic interactions using an industry standard non-backdrivable manipulator, a control law was developed to have the vehicle-manipulator system passively interact with its environment, by mimicking an arrangement of masses, springs, and dashpots. This control law was tested and analyzed in a simple experiment that achieved a 90% reduction in settling time. Daniel for the constant reminder that everything will be alright, and Ray for always making that possible in more ways than imaginable. Finally, the author would like to thank Prof. Franz Hover for having gone above and beyond his role as an advisor from the start, and without whom none of this would have been possible. 5 6

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Section: Distance Minimizationmentioning

confidence: 99%

Navigation and manipulation for autonomous underwater dismantling of offshore structures

Welch¹

2015

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“…(Williams et al, 2000), (Hernàndez et al, 2009), and (Fairfield et al, 2006)). The work of Thurn (Thrun et al, 2005) includes a good survey of the core techniques capable of fusing data from multiple sensors to create maps.…”

Section: Mapping Via Underwater Robot Systemsmentioning

confidence: 99%

Uncertainty Visualization and Hole Filling for Geometric Models of Ancient Water Systems

Forrester¹,

McVicker²,

Gambin³

et al. 2013

Proceedings of the International Conference on Computer Graphics Theory and Applications and International Conference on Inform

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Abstract:Geometric data acquired via a scanning process can suffer from holes due to errors in the acquisition process, noise, or challenges in merging multiple inputs together into a unified map. We present a straight forward algorithm to fill holes in incomplete evidence grids representing acquired geometric data. We also present our methods to apply learning in order to statistically evaluate the proposed hole filling algorithm. This analysis validates our proposed method for hole filling and additionally enables the construction of a probability distribution function to represent the accuracy of the filled data per model. During surface reconstruction, this function can be used to visualize the certainty of the filled geometry via transparency and coloring giving the user an understanding of the data's accuracy. This work is motivated by a multi-year project to construct educational visualizations of ancient water storage systems, i.e. cisterns and wells within churches, fortresses and homes on the islands of Malta, Gozo and Sicily.

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“…Although the method is suitable for laser data, the same authors have noted that for sparse noisy data like sonar, better results can be achieved using the ICNN data association algorithm instead of using the virtual point (spIC). A reduced version of the spIC algorithm is used in this paper, being extended with the MSISpIC algorithm proposed in [12], to dial with data gathered by an AUV utilizing MSIS. Hence, an EKF using a constant velocity model with acceleration noise, updated with velocity and attitude measurements obtained from a DVL and a MRU respectively, is used to estimate the trajectory followed by the robot along the scan.…”

Section: Introductionmentioning

confidence: 99%

Pose-based SLAM with probabilistic scan matching algorithm using a mechanical scanned imaging sonar

et al. 2009

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Abstract-This paper proposes a pose-based algorithm to solve the full SLAM problem for an Autonomous Underwater Vehicle (AUV), navigating in an unknown and possibly unstructured environment. The technique incorporate probabilistic scan matching with range scans gathered from a Mechanical Scanning Imaging Sonar (MSIS) and the robot dead-reckoning displacements estimated from a Doppler Velocity Log (DVL) and a Motion Reference Unit (MRU). The proposed method utilizes two Extended Kalman Filters (EKF). The first, estimates the local path travelled by the robot while grabbing the scan as well as its uncertainty and provides position estimates for correcting the distortions that the vehicle motion produces in the acoustic images. The second is an augment state EKF that estimates and keeps the registered scans poses. The raw data from the sensors are processed and fused in-line. No priory structural information or initial pose are considered. The algorithm has been tested on an AUV guided along a 600m path within a marina environment, showing the viability of the proposed approach.

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MSISpIC: a probabilistic scan matching algorithm using a mechanical scanned imaging sonar

Cited by 31 publications

References 16 publications

Navigation and manipulation for autonomous underwater dismantling of offshore structures

Navigation and manipulation for autonomous underwater dismantling of offshore structures

Uncertainty Visualization and Hole Filling for Geometric Models of Ancient Water Systems

Pose-based SLAM with probabilistic scan matching algorithm using a mechanical scanned imaging sonar

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