Three-dimensional space perception is one of the most important capabilities for an autonomous mobile robot in order to operate a task in an unknown environment adaptively since the autonomous robot needs to detect the target object and estimate the 3D pose of the target object for performing given tasks efficiently. After the 3D point cloud is measured by an RGB-D camera, the autonomous robot needs to reconstruct a structure from the 3D point cloud with color information according to the given tasks since the point cloud is unstructured data. For reconstructing the unstructured point cloud, growing neural gas (GNG) based methods have been utilized in many research studies since GNG can learn the data distribution of the point cloud appropriately. However, the conventional GNG based methods have unsolved problems about the scalability and multi-viewpoint clustering. In this paper, therefore, we propose growing neural gas with different topologies (GNG-DT) as a new topological structure learning method for solving the problems. GNG-DT has multiple topologies of each property, while the conventional GNG method has a single topology of the input vector. In addition, the distance measurement in the winner node selection uses only the position information for preserving the environmental space of the point cloud. Next, we show several experimental results of the proposed method using simulation and RGB-D datasets measured by Kinect. In these experiments, we verified that our proposed method almost outperforms the other methods from the viewpoint of the quantization and clustering errors. Finally, we summarize our proposed method and discuss the future direction on this research. 

/pdf/growing-neural-gas-with-different-topologies-for-3d-space-23qzlcj6.pdf

Growing Neural Gas with Different Topologies for 3D Space Perception

The use of photogrammetry provides an inexpensive, alternative method that can simplify the processes traditionally carried out in the orthotics workshop. The objectives of this study are to develop a method based on photogrammetry to obtain 3D-printed positive foot casts for fabricating thermoconformed orthoses from a negative cast in phenolic foam. Using a basic Smartphone, a photo capture protocol for feet, free software and a 3D printer, we tested the suitability of the positive cast obtained to fabricate custom foot orthoses using thermoconformed 3 mm polypropylene in the orthotics laboratory. The results show that digitally fabricated casts provide a very close replicate of the positive casts obtained traditionally through plaster casting (maximum dimension discrepancy between casts of 2 mm in length and 0.4 mm in forefoot, midfoot and rearfoot measurements). They are also suitable for the process of fabricating 2- and 3-mm polypropylene thermoconformed plantar orthoses. Photogrammetry can be used as a new method to obtain a positive 3D foot cast suitable for fabricating custom orthoses, in a valid, safe, cleaner and more lasting procedure that removes the process of plaster casting.

/pdf/using-photogrammetry-to-obtain-3d-printed-positive-foot-2gzns7ji.pdf

Using Photogrammetry to Obtain 3D-Printed Positive Foot Casts Suitable for Fitting Thermoconformed Plantar Orthoses

Body ruler parameters are important indicators to evaluate the growth status of finishing pigs. In view of the problems such as single measurement parameter and large error of measurement results in the measurement of pig body ruler. In this paper, the depth camera Kinect V2 is used to obtain local point cloud data from the above and left and right sides. Through point cloud denoising, point cloud reduction and point cloud segmentation related processing. Using the improved ICP point cloud registration. Then we used accurate estimation techniques for the point cloud data. After experimental measurements at different angles. In the pig body data, the average relative error of body length was 4.63%, body height 3.87%, body width 2.87%, hip height 2.51%, hip width 1.86%. The experimental results demonstrate the effectiveness of the present method.

Three-dimensional point cloud reconstruction and body ruler measurement of pig body under multi-angle KinectV2

In clinical practice, specific customization is needed to address foot pathology, which must be disease and patient-specific. To date, the traditional methods for manufacturing custom functional Foot Orthoses (FO) are based on plaster casting and manual manufacturing, hence orthotic therapy depends entirely on the skills and expertise of individual practitioners. This makes the procedures difficult to standardize and replicate, as well as expensive, time-consuming and material-wasting, as well as difficult to standardize and replicate. 3D printing offers new perspectives in the development of patient-specific orthoses, as it permits addressing all the limitations of currently available technologies, but has been so far scarcely explored for the podiatric field, so many aspects remain unmet, especially for what regards customization, which requires the definition of a protocol that entails all stages from patient scanning to manufacturing.A feasibility study was carried out involving interdisciplinary cooperation between industrial engineers and podiatrists. To that end: (i) For patient-specific data acquisition, 3D scanning of the foot is compared to traditional casting. (ii) a modelling GD workflow is first created to design a process permitting easy creations of customized shapes, enabling the end user (the podiatrist) to interactively customize the orthoses. Then, (iii) a comparison is made between different printing materials, in order to reproduce the same mechanical behavior shown by standard orthoses. To do this, the mechanical properties of standard materials (Polycarbonate sheets), cut and hand-shaped, are compared with four groups of 3D printed samples: poly(ethylene glycol) (PETG), poly(acrylonitrile-butadiene.styrene) (ABS), polycarbonate (PC) and poly(lactic acid) (PLA) obtained by Fused Filament Fabrication (FFF).Differences found between the foot plaster model obtained with the plaster slipper cast in a neutral position and the model of the real foot obtained with 3D scanning in the same position can be ascribed to the non-stationarity of the patient during the acquisition process, and were limited by a locking system with which no substantial differences in the almost entire sole of the foot scan were observed.Using the designed GD workflow, podiatrists with limited CAD skills can easily design and interactively customize foot orthoses to adapt them to the patients' clinical needs. 3D printing enables the complex shape of the orthoses to be reproduced easily and quickly. Compared to Polycarbonate sheets (gold standard), all the printed materials were less deformable and reached lower yield stress for comparable deformation. No modifications in any of the materials as a result of printing process were observed. 

https://www.mdpi.com/1996-1944/15/12/4064/pdf?version=1654673641

Foot Orthosis and Sensorized House Slipper by 3D Printing

In a three-dimensional (3D) foot scanning, a 3D point cloud is generated and meshed to create a 3D foot model with depth information. In the previous analog process of foot scanning is to draw an outline of the foot and imitate the foot directly. This method has some disadvantage that has a measurement error, difficult to recreate, inaccuracy of reference point and an error by an expert abilities. In this paper, in-plane deformation measurement method is proposed to solve this problem. In-plane deformation measurement method is a novel method to measure foot size from a 3D foot scanning data. The Shrink-Wrap method is used to reconstruct a foot model, that estimate the foot model by wrapping the surface of a foot of the square template mesh model. For comparison, foot length, foot width and height of the instep is measured with the proposed method. In comparison with handcrafted method, the experimental results show that our proposed method has complexity reduction, higher precision and accurate reproducibility.

Foot Measurement Using 3D Scanning Model

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Foot Measurement Using 3D Scanning Model