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Decentralised and Centralised Fixed Structure H∞ Robust Loop Shaping for the MIMO Microsurgical Manipulation Based on PSOGSA
(2026-01-01)
Kaitwanidvilai, Somyot
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Konghuayrob, Poom
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Aoyama, Hisayuki
This paper presents decentralised and centralised fixed-structure H∞ robust control methods optimised by the Particle Swarm Optimisation and Gravitational Search Algorithm (PSOGSA) for a coupled multi-input multi-output (MIMO) microsurgical manipulator. The design framework explicitly considers uncertainties and disturbance constraints. Conventional H∞ loop-shaping controllers are typically of high order, complex, and difficult to implement in practice. To address this limitation, Proportional-Integral-Derivative (PID)-structured decentralised and centralised H∞ controllers are proposed, providing compact structures while retaining robustness. The novelty of this work lies in embedding H∞ robustness criteria into practical PID-based frameworks, bridging the gap between theoretical robust design and experimental implementation in microsurgical applications. The proposed controllers are evaluated against a reduced-order H∞ controller derived from Hankel norm approximation and a Ziegler–Nichols tuned PID controller, using both simulation and experimental studies. Results demonstrate that the proposed controllers achieve improved stability margins (0.449–0.521 compared with 0.436 for the reduced-order design), maintain low root-mean-square errors (≈0.067–0.089) and remain robust under voltage disturbances where conventional PID control fails. These findings confirm the contribution of a practical and efficient robust control strategy for enhancing the precision and reliability of microsurgical manipulators.
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Optical-based foot plantar pressure measurement system for potential application in human postural control measurement and person identification
(2021-07-01)
Keatsamarn, Tanapon
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Visitsattapongse, Sarinporn
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Aoyama, Hisayuki
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Pintavirooj, Chuchart
Plantar pressure, the pressure exerted between the sole and the supporting surface, has great potentialities in various research fields, including footwear design, biometrics, gait analysis and the assessment of patients with diabetes. This research designs an optical-based foot plantar pressure measurement system aimed for human postural control and person identification. The proposed system consists of digital cameras installed underneath an acrylic plate covered by glossy white paper and mounted with LED strips along the side of the plate. When the light is emitted from the LED stripes, it deflects the digital cameras due to the pressure exerted between the glossy white paper and the acrylic plate. In this way, the cameras generate color-coded plantar pressure images of the subject standing on the acrylic-top platform. Our proposed system performs personal identification and postural control by extracting static and dynamic features from the generated plantar pressure images. Plantar pressure images were collected from 90 individuals (40 males, 50 females) to develop and evaluate the proposed system. In posture balance evaluation, we propose the use of a posture balance index that contains both magnitude and directional information about human posture balance control. For person identification, the experimental results show that our proposed system can achieve promising results, showing an area under the receiver operating characteristic (ROC) curve of 0.98515 (98.515%), an equal error rate (EER) of 5.8687%, and efficiency of 98.515%.
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Hybrid facial features with application in person identification
(2020-08-14)
Purahong, Boonchana
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Chutchavong, Vanvisa
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Aoyama, Hisayuki
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Pintavirooj, Chuchart
This paper presents the hybrid facial feature with identification and verification based on facial images. A query facial image had been taken under different conditions of the facial image of the same person (as the query). The query facial image database was constructed. We have used the technique of three-dimensional (3D) Dlib facial landmarks using a direct linear transform technique. A set of absolute affine invariance had been constructed from a series of the 3D landmark quadruplets, which make the facial identification robust to affine geometric transformation. These 3D facial features serve as a coarse feature depending on each individual facial structure. The construct of the 2D detail features represents the edge facial image confined between the 2D Dlib landmarks. The similarity of the 2D feature is achieved by aligning the 2D query edge image against that of the reference edge image. The geometric transformation matrix is estimated from the 2D Dlib landmarks, where correspondence is well established. An identification/verification cost function using a combination of local 2D facial features and global 3D facial features is utilized to verify and identify a query facial image against a candidate facial image(s). The performance of the algorithm yielding an area of 99.97% perfect classification is represented as a value under the receiver operating characteristic (ROC) curve.
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Optical-based foot plantar pressure measurement with application in human postural balance, gait and recognition analysis
(2020-07-01)
Keatsamarn, Tanapon
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Visitsattapongse, Sarinporn
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Pintavirooj, Chuchart
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Aoyama, Hisayuki
In this research, we purposed the design of real-time low-cost marker-free optical-based plantar-pressure measurement with application in human postural control, gait and recognition analysis. The system consists of a series of digital cameras capture installed underneath the acrylic-top platform. Light of LED strip mounted along the side of the acrylic plate deflected by the pressure exerted between the glossy white paper installed in the top of acrylic and the acrylic plate to the digital cameras provides the color-coded plantar pressure image of the subject standing on the platform. The system can provide both static features and dynamic features. Our hybrid system consists of a series of USB cameras aligned under the acrylic-plate walking platform. The mosaic image processing is used to concatenate the captured image to increase the sensing area. Captured the image data in video mode, various dynamic parameters can be derived for further dynamic analysis. The image capturing in one specific frame can be used for static analysis. Application in human-postural measurement, gait analysis, and person identification indicate that our system is an all-in-one system for plantar pressure measurement.
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Vein pattern verification and identification based on local geometric invariants constructed from minutia points and augmented with barcoded local feature
(2020-05-01)
Pititheeraphab, Yutthana
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Thongpance, Nuntachai
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Aoyama, Hisayuki
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Pintavirooj, Chuchart
This paper presents the development of a hybrid feature-dorsal hand vein and dorsal geometry-modality for human recognition. Our proposed hybrid feature extraction method exploits two types of features: dorsal hand geometric-related and local vein pattern. Using geometric affine invariants, the peg-free system extracts minutia points and vein termination and bifurcation and constructs a set of geometric invariants, which are then used to establish the correspondence between two sets of minutiae-one for the query vein image and the other for the reference vein image. When the correspondence is established, geometric transformation parameters are computed to align the query with the reference image. Once aligned, hybrid features are extracted for identification. In this study, the algorithm was tested on a database of 140 subjects, in which ten different dorsal hand geometric-related images were taken for each individual, and yielded the promising results. In this regard, we have achieved an equal error rate (EER) of 0.243%, indicating that our method is feasible and effective for dorsal vein recognition with high accuracy. This hierarchical scheme significantly improves the performance of personal verification and/or identification.
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Robot arm structure design using polyamide evaluated by finite element analysis
(2020-01-01)
Kaitwanidvilai, Somyot
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Buthgate, Siwawong
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Aoyama, Hisayuki
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Konghuayrob, Poom
Robots have increasingly replaced humans for many jobs, including 24 h work, routine tasks, and dangerous jobs. However, the robot operating system has high power consumption in many processes. This has led to energy efficiency being the main focus. We have opted to build a robot with high strength, light weight, and low power consumption by reducing the weight of its components. Presently, we know that the structure of most robots in the world is made of metals, plastics, and composite materials. In this research, we designed the mechanical structure of robot arms with three different materials (cast iron, polyamide, and aluminum) using the finite element method to analyze and evaluate the possibilities of these materials. The dynamic load, power consumption, and mechanical characteristics were compared. It was found that polyamide could help lighten the weight by 40% and increase energy efficiency along with cost effectiveness by 41%. Although polyamide is particularly easy to find, cast iron is stronger than polyamide.
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Personal identification using a delaunay triangle and optic disc retinal vascular pattern
(2020-01-01)
Kanjanasurat, Isoon
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Purahong, Boonchana
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Aoyama, Hisayuki
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Benjangkaprasert, Chawalit
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Pintavirooj, Chuchart
Retinal vascular patterns are unique and individual. They provide highly secure and correct identity authentication. In this study, we exploit an image alignment approach based on a geometric invariant, which is the area spanned by feature-point triplets for personal identification. First, we located the optic disc by using a projection of the vascular structure in vascular extraction and extracted feature points that are bifurca- tions of a retinal blood vessel in the vicinity of the optic disc as the landmarks. Delaunay triangulation is then applied to the extracted feature points. The absolute invariant is then derived by taking the ratio of successive triangular area patches. The alignment is achieved by establishing correspondences between feature points after a conformal sort- ing step based on a derived set of absolute affine invariants. The affine transformation parameters can then be calculated by the corresponding vertices of the most robust neigh- bouring triangle of both inquiry and reference images. The optic disc localization results successfully located 95.95% in six widely used retinal image databases. The algorithm of vascular extraction, applied on the DRIVE database, provided an average accuracy of ap- proximately 94.1%. The best accuracy and sensitivity for neighbouring triangle matching obtained were 99.90% and 87.66%, respectively.

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