Comparative Performance Tests Research Articles

Comparative analysis of single-board computers for the development of a microarchitectural computing system for fire detection

Objectives. The purpose of the work is to select the basic computing microplatform of the onboard microarchitectural computing complex for the detection of anomalous situations in the territory of the Republic of Belarus from space on the basis of artificial intelligence methods.Methods. The method of comparative analysis is used to select a computing platform. A series of performance tests and comparative analysis (benchmarking) are performed on the selected equipment. The methods of comparative and benchmarking analysis are performed in accordance with the terms of reference to the current project.Results. A comparative analysis and performance testing of Raspberry Pi 4 Model B and Cool Pi 4 Model B single-board computers, as well as AI-accelerator Google Coral USB Accelerator with Google Edge TPU have been performed. The comparative analysis showed that Raspberry Pi 4 Model B and Cool Pi 4 Model B fully meet the terms of reference to the current project. At the same time Cool Pi 4 Model B handles neural network calculations well, but four times slower than similar calculations on Google Coral USB Accelerator. Neural network computations on the Raspberry Pi 4 Model B are 22 times slower than similar computations on the Google Coral USB Accelerator. Cool Pi 4 Model B outperforms Raspberry Pi 4 Model B by the factor of two to three for data copying and compression and almost six times faster for neural network computations.Conclusion. Despite the fact that Raspberry Pi 4 Model B meets the terms of reference to the project as a computational basis, when developing an on-board microarchitectural computing system for detecting anomalous situations, it is worth using more powerful alternatives with built-in AI-accelerators (e.g., Radxa Rock 5 Model A) or with an additional external AI-accelerator (e.g., a combination of Cool Pi 4 Model B and Google Coral USB Accelerator). Using a Raspberry Pi 4 Model B with an additional AI-accelerator is also acceptable and will speed up computations by several dozen times. AI-accelerators provide the fastest neural network computations, but there are features related to the novelty of the technology that will be explored in further development.

The Mechanical Analysis and Comparative Performance Test of the Roller-Type Pulling Mechanism for the Whole Cotton Stalk Pulling Machine

In order to address the common difficulties in pulling and harvesting whole cotton stalks, such as high pulling resistance, high miss-pulling rate, and high breakage rate, which severely hinder the recycling of cotton stalks, three different pulling mechanisms with different pulling principles (wrapping-type pulling mechanism, clamping-type pulling mechanism, transverse roller-type pulling mechanism) were designed. The pulling force on cotton stalks during the pulling process of the three different roller-type pulling mechanisms was compared and analyzed, clarifying the mechanism of roller-type whole cotton stalk pulling mechanisms and identifying situations with optimal pulling force. Field comparative experiments were conducted to compare the working performance of different roller-type pulling mechanisms in the field, and a comprehensive analysis of two key indicators in pulling cotton stalks, miss-pulling rate and breakage rate, was carried out. The results showed that the pulling method and pulling force of the pulling mechanism played a crucial role in the successful pulling of cotton straws. Comparative analysis of the three pulling mechanisms revealed that the clamping-type pulling mechanism had the highest pulling force. The standard deviation means of the missed pull rates for mechanisms X1, X2, and X3 were 0.83%, 0.59%, and 0.43%, respectively, while the standard deviation means of the breakage rates were 1.48%, 1.79%, and 0.49%, respectively. The enveloping-type pulling mechanism had a higher missed pull rate with an average of 8.32%, and the clamping-type pulling mechanism resulted in excessive breakage of cotton straw during operation, with an average breakage rate of 14.10%. In contrast, the transverse roller-type straw pulling mechanism performed the best in the field performance test, as it did not require precise alignment and had an average missed pull rate of 4.55% and an average breakage rate of only 7.55%. Considering the practical needs of agriculture production, the transverse roller-type straw pulling mechanism is recommended as the pulling device for cotton straw harvesting. The research results can provide a reference for the design selection of whole-plant straw pulling mechanisms.

Comparative Performance Testing of the Impact of ACK Loss in TCP Tahoe, TCP Reno, and TCP New Reno on the ns-2 Simulator

In TCP/IP networks, TCP provides reliable delivery service with the guarantee that packets sent reach their destination. This is achieved through the use of acknowledgments (ACK) as a mechanism. In TCP/IP networks, TCP provides reliable delivery service with the guarantee that packets sent reach their destination. This is achieved through the use of acknowledgments (ACK) as a mechanism. In all three variants of TCP, they rely on the presence of ACK packets. Therefore, testing will be conducted to observe the effect of ACK loss on TCP performance. The testing involves introducing disruptive traffic on the ACK path with varying magnitudes. This disruptive traffic results in the loss of some ACK packets, depending on the magnitude of the disruptive traffic. The testing was conducted using the ns-2 simulator software. The research findings indicate that the loss of ACK packets leads to a decrease in TCP performance. TCP Reno successfully improves the performance of TCP Tahoe, but the algorithm improvement in TCP New Reno does not have an effect on TCP Reno..

Experimental and Numerical Study of the Flexural Performance of Spontaneous Combustion Gangue Coarse Aggregate Concrete Laminated Slab

(1) Background: to study the differences in flexural performance and failure characteristics of spontaneous combustion gangue coarse aggregate concrete (SCGAC) laminated slabs and ordinary concrete laminated slabs, comparative flexural performance tests of one ordinary concrete laminated slab and four spontaneous combustion gangue coarse aggregate concrete laminated slabs (SCGACLSs) full-scale specimens were carried out. (2) Methods: The loading method was four-point unidirectional static loading; the failure mode, load–deflection curve, load–reinforcement strain curve, and load–concrete strain curve of each specimen were analyzed. In addition, the load–deflection curve of the five slabs were predicted by ABAQUS. (3) Results: The five laminated slabs showed similar behaviors in terms of failure mode, load–strain curve, load–deflection curve, and deformation and all the properties satisfied the Chinese standard GB50010 (2010). Compared with ordinary concrete laminated slabs, the cracking load of SCGACLS with a precast layer of SCGAC(C30) decreased by 15.2% and the span deflection increased by 28.3% in the ultimate condition; however, when the strength grade of SCGAC of the precast layer was increased to SCGAC(C40), the cracking load increased by 7.8% and the span deflection was similar to that of the ordinary concrete laminated slabs. All specimens conformed to the planar section assumption. In addition, the finite element model (FEM) prediction results showed that the maximum relative errors of load and deflection were <5% and <10%, respectively, indicating that the established FEM had high prediction accuracy. (4) Conclusions: The defects of reduced load-carrying capacity and uncoordinated deformation caused by the different elastic modulus of precast and cast-in-place layer concrete can be compensated by appropriately increasing the strength grade of precast layer concrete of SCGACLSs. The application of SCGACLSs in structures is feasible.

Automated Fish Detection and Tracking System Using Pre-Trained Mask R-CNN for Ecological Biodiversity

Introduce a new dynamic classifying algorithm in this paper to recognize and monitor fish activity to simultaneously better comprehend their synapomorphies. The pre-trained Mask Regional Convolutional Neural Network (Mask-R-CNN) is trained using a set of test models extracted from recorded video recording. The approach suggested subsequently yields well-enhanced feature vectors. The system’s automatic fish detection and tracking capabilities are improved, enhancing underwater investigation for supervising ecological biodiversity. The publicly accessible field-truth dataset assesses recall, F1-score, and classification and tracking precision. Utilizing current tracking R-CNN algorithms like Lowest Output Sum of Siamese Mask (SiamMask), Sequential Non-Maximum Suppression (Seq-NMS), and Squared Errors (MOSSE), comparative performance testing is conducted. In comparison to Siam-Mask (84%), Seq-NMS (78%) and MOSSE (75%), more than 120 of 170 specific bream were detected using the pre-trained Mask-R-CNN of the proposed algorithm (87%). This pre-trained Mask R-CNN system was used in the evaluation, and it was discovered that detection and tracking accuracy had increased significantly. This suggests that the ocean ecosystem could benefit from applying the proposed approach for management of ecology.

Compressible Cellulose Wood Prepared with Deep Eutectic Solvents and Its Improved Technology

Elastic materials have a wide range of applications in many industries, but their widespread use is often limited by small-scale production methods and the use of highly polluting chemical reagents. In this study, we drew inspiration from research on wood softening to develop an environmentally friendly and scalable approach for producing a new type of compressible wood material called CW from natural wood. To achieve this, we employed a top-down approach using a novel type of "ionic liquid" eutectic solvent (DES) that is cost-effective, environmentally friendly, and recyclable. After treatment with DES, the resulting CW demonstrated good elasticity and durable compressibility, which was achieved by removing some lignin and hemicellulose from the wood and thinning the cell walls, thereby creating a honeycomb structure that allows for sustained compression and rebound. However, we found that the wood treated with a single eutectic solvent showed some softening (CW-1), although there was still room for further improvement of its elasticity. To address this, we used a secondary treatment with sodium hydroxide alkali solution to produce a softer and more elastic wood (CW-2). We conducted a series of comparative analyses and performance tests on natural wood (NW) and CW, including microscopic imaging; determination of chemical composition, mechanical properties, and compressive stress effects; and laser confocal testing. The results show that the DES and sodium hydroxide alkali solution treatments effectively removed some lignin, hemicellulose, and cellulose from the wood, resulting in the thinning of the cell walls and creating a more elastic material with a sustainable compression rebound rate of over 90%. The various properties of CW, including its elasticity, durability, and sustainability, provide great potential for its application in a range of fields, such as sensors, water purification, and directional tissue engineering.

Comparative education or epistemological power games for world domination

ABSTRACT This article argues that the worlds which comparative education has explored and is exploring are characterised by three main political patterns. The first and oldest is the competitive nation-state as the starting point of the comparison, an educationalised nation-state, one whose relative global strength in economy and military prowess is attributed to the education system. The second pattern, easily visible in the Cold War, is the idea of an almost standardised progression, linked to economic, military and thus geopolitical power. And the contemporary pattern is that this nexus of global potency and education can be broken down into comparative school performance tests (for example in PISA currently) through which reform needs (almost automatically) are formulated at home, and elsewhere. If this analysis and its history – which is illustrated in the following – is even approximately accurate, ‘comparative education’ may need to re-think some of its basic assumptions about itself.

Revisions of evidence-based governance: The case of the Austrian quality management system SQA

Throughout the last 30 years, many European countries have ‘modernized’ their governance of education. For the Central European school systems of Austria and the German Bundesländer it has been claimed that this ‘modernization’ was characterised by a sequence of reform ‘waves’ which culminated in introducing ‘evidence-based governance’ models characterised by nation-wide comparative performance testing, new school inspections, etc. This paper argues that we recently see the emergence of revisions of the original ‘evidence-based governance’ models which may be understood as a new ‘wave of modernization’ of school governance. These models aim to react to increasing criticism of the evidence-based philosophy, in particular to its ambivalent attitude to teacher professionalism. The paper at hand analyses the specific aspirations and features of ‘revised evidence-based governance instruments’ to discuss their potential as a policy future. In a second step, we take the Austrian quality management system SQA as an example for these new governance models. In an explorative study, we use case data to understand how teachers and school leaders evaluate this reform and its impact on their work. In particular, we are interested whether or not educational professionals feel that this reform conveys appreciation of and trust in their professional capacities.

Designing a supervised feature selection technique for mixed attribute data analysis

Identifying optimal features is critical for increasing the overall performance of data classification. This paper introduces a supervised feature selection technique for analyzing mixed attribute data. It measures data classification performances of features with a user-defined performance criterion and determines optimal features to boost the overall data analysis performance. A performance evaluation is managed to highlight the usefulness of the technique with existing feature selection techniques such as analysis of variance test, chi-square test, principal component analysis, and mutual information. Visualization is also utilized to understand the differences in classifying instances with different features. From a comparative performance testing and evaluation, we found 5 ∼ 10% performance improvements with the proposed technique. Overall, evaluation results showed the usefulness of our proposed feature selection technique in mixed attribute data analysis.

Comment on Scheepers et al. Comparative Performance Testing of Respirator versus Surgical Mask Using a Water Droplet Spray Model. Int. J. Environ. Res. Public Health 2021, 18, 1599.

In the article "Comparative Performance Testing of Respirator versus Surgical Mask Using a Water Droplet Spray Model" by Scheepers et al. [...].

Inferential‐ and measurement‐based methods to estimate rooftop “solar city” potential in megacity Seoul, South Korea

AbstractData analysis and collection techniques now allow for detailed inventory‐building of urban rooftops for the purposes of identifying solar energy potential within geographically defined boundaries, including those of cities. The complexity and inherent diversity of a city's building stock has propelled the introduction of many so‐called “solar city” assessment methods that, with varying levels of accuracy, scalability, and ease of use, seek to characterize the citywide solar photovoltaic (PV) resource potential. A review of the landscape of available methods supports a fundamental distinction across two classes of methods. First, “solar city” assessment methods can principally rely on inference to identify and characterize rooftop solar potential. Such inferential methods can establish estimates of citywide solar potential without needing direct insight into rooftop conditions or morphology, Second, measurement‐based methods estimate rooftop solar opportunities based on the direct measurement of rooftop conditions, often conducted through remote sensing. Comparative performance testing of several inferential‐ and measurement‐based methods using case study analysis underscores the importance of measurement‐based methods. In particular, measurement‐based methods are likely better positioned to support the needs of policy‐makers and investors interested in transforming a city or metropolitan area into a sustainable city whose buildings serve as the host of a new solar PV‐powered distributed electricity service system.This article is categorized under: Sustainable Energy > Solar Energy Energy and Power Systems > Energy Infrastructure Cities and Transportation > Smart Cities

Effects of nanomaterials on Cs3Sb photocathode emission performance

A new approach to preparing the cesium antimonide photocathode has been developed. A tungsten sponge diffusion barrier layer, instead of the conventional nickel pipe, was used as the evaporation source so that a slow and uniform evaporation of the photoemissive materials, whose direction and amount could be well controlled, was realized. Then, the cathode substrate surface was modified with a nanoparticle layer, resulting in better photoemissive material adsorption and higher light absorbance. A new technique of treating the tungsten sponge, which worked as the barrier layer to the diffusion of the photoemissive materials, was studied. The tungsten–copper alloy was subjected to direct high-frequency heating in a vacuum chamber so that the copper in the alloy evaporated rapidly, resulting in smooth and shiny tungsten sponge. In comparison with the conventional method for fabricating the tungsten sponge, in which the copper in the tungsten–copper alloy was removed chemically, the new method removed the copper more completely, took less time, and caused less pollution. By means of direct-current magnetic sputtering, a layer of osmium nanoparticles of 50 nm diameter was deposited on the photocathode substrate surface. Then, a diode tube for the photocathode emission test equipped with a small titanium ion pump, whose pressure was as low as 5 × 10−8 Pa, was developed. A comparative emission performance test was carried out on the photocathode with the substrate surface covered with an osmium film vs that covered with osmium nanoparticles. The highest quantum efficiencies of the stable photoemission from the two photocathodes were 1.80 × 10−3 and 5.13 × 10−3, respectively. Moreover, the light absorptivity of the osmium nanoparticle-coated photocathode was 2.16 times that of the osmium film-coated photocathode, and the quantum efficiency of the former was 2.85 times that of the latter. Therefore, the improvement in the quantum efficiency of the osmium nanoparticle-coated photocathode is mainly attributed to the increase in the light absorptivity.

Insight into the effect of mass transfer channels and intrinsic reactivity in titanium silicalite catalyst for one-step epoxidation of propylene

One-step epoxidation of propylene to propylene oxide (PO) in TS-1/H2O2 system is a promising green and sustainable formation route. However, the TS-1 catalyst is limited by the small pore channels and inadequate intrinsic reactivity. Herein, tetrapropylammonium hydroxide (TPAOH) is used to modify the TS-1 skeleton structures to improve the mass transfer and intrinsic reactivity. Comparative catalytic performance tests indicate that the optimized temperature for TPAOH treatment to modify TS-1 was 90 °C, and the achieved H2O2 utilization efficiency and the PO selectivity can be over 80%. Different TPAOH treatment temperatures significantly influenced the dissolution and recrystallization behavior of TS-1, which altered the composition and microstructure in terms of the pore volume and size, surface properties, and active sites. Our findings indicated that the enlarged pore channels for favorable mass transfer, improved hydrophobic surfaces, enriched framework titanium, and reduced acid strength of titanium silicalite zeolite should be the primary reasons for the enhanced conversion and yields.

Selective Subject Pooling Strategy to Improve Model Generalization for a Motor Imagery BCI.

Brain–computer interfaces (BCIs) facilitate communication for people who cannot move their own body. A BCI system requires a lengthy calibration phase to produce a reasonable classifier. To reduce the duration of the calibration phase, it is natural to attempt to create a subject-independent classifier with all subject datasets that are available; however, electroencephalogram (EEG) data have notable inter-subject variability. Thus, it is very challenging to achieve subject-independent BCI performance comparable to subject-specific BCI performance. In this study, we investigate the potential for achieving better subject-independent motor imagery BCI performance by conducting comparative performance tests with several selective subject pooling strategies (i.e., choosing subjects who yield reasonable performance selectively and using them for training) rather than using all subjects available. We observed that the selective subject pooling strategy worked reasonably well with public MI BCI datasets. Finally, based upon the findings, criteria to select subjects for subject-independent BCIs are proposed here.

Cooking small and large portions of “biodiversity‐soup”: Miniaturized DNA metabarcoding PCRs perform as good as large‐volume PCRs

AbstractDNA metabarcoding is a powerful tool to assess arthropod diversity in environmental bulk samples such as Malaise trap, pitfall trap, or hand net samples. While comparative performance tests for different extraction protocols, primers, and Taq polymerases have been made, the effect of different PCR volumes on bulk sample metabarcoding performance is less explored. Although using small PCR volumes reduces overall costs, they may lead to decreased taxon recovery or higher replicate variability due to increased pipetting imprecision, PCR stochasticity (PCR drift), or inhibition when using high amounts of template community DNA. We here performed a simple DNA metabarcoding experiment to test if species detection and the consistency of technical replicates decrease with decreasing PCR volume in standard reaction tubes. We used a mock community sample consisting of different amounts of DNA from 35 arthropod species, and a Malaise trap sample composed of many thousand insect specimens. PCR volumes tested were 5, 10, 15, 20, 25, and 50 µl. Both samples were replicated 14 times in the first PCR step with two technical replicates each in the second PCR step. Our data show that small PCR volumes did neither have systematically lower species detection or richness values, nor lower consistency between PCR replicates. We therefore recommend low volumes primarily depending on handling constraints. Further, we emphasize the importance of sequencing depth for taxon recovery.

A Smart Interface HUD Optimized for VR HMD and Leap Motion

Abstract Virtual reality head-mounted displays (VR HMDs) can provide three-dimensional content to increase user immersion that is relatively acceptable. However, user interactions with VR HMDs often do not satisfy a virtual environment. In this article, the authors propose a smart human‐computer interaction technique that runs on VR HMDs and Leap Motion. In this study, they focused on improving interaction methods for VR content and providing interfaces and information necessary for the operation of such content in a user-friendly manner, which should reduce fatigue and dizziness. To this end, they propose and validate a smart head-up display that is suitable for VR content. Specifically, a virtual head-up display (HUD) was designed and optimized for use with VR HMD and Leap Motion technologies. Additionally, they present comparative performance tests to validate the proposed system.

Water vapor transmission properties of acrylic organic coatings

In this work, we evaluate the water vapor transmission rate (WVTR), the permeability (P), solubility (S), and diffusion (D) coefficients of Paraloid B44, Paraloid B72, and Incralac coatings in the temperature range of 5–35°C. The Arrhenius function—diffusion activation energy and preexponential factor—has also been determined from the data: D_{B44} = 35.2;{text{cm}}^{2} ;{text{s}}^{ - 1} exp left( { - 25;{text{kJ mol}}^{ - 1} /{text{RT}}} right); D_{B72} = 9.5;{text{cm}}^{2} ;{text{s}}^{ - 1} exp left( { - 23;{text{kJ mol}}^{ - 1} /{text{RT}}} right); D_{text{Incralac}} = 622.8;{text{cm}}^{2} ;{text{s}}^{ - 1} { exp }left( { - 28;{text{kJ mol}}^{ - 1} /{text{RT}}} right). These resins are important coating materials, for example, for conservators to protect metallic artifacts, such as statues, against corrosion. Despite Paraloid B44 and B72 resins being considered as reference materials in conservation practice, that is, new coating materials (either water vapor retarders or transmitters) are often compared to them, there are no comprehensive data for the quantities describing the vapor permeability (P, S, D) of these materials. The measurements are based on the ISO cup-method using substrate/coating composite samples. The strength of this technique is that it can also be used when the coating is non-self-supporting; nevertheless, P, S, and D can be deduced for the coating layer itself, and it seems to be a standardizable procedure for comparative performance testing of coating materials. Paraloid B72 layers exhibited higher WVTRs—from 39 to 315 g m−2 day−1 as the temperature increased from 5 to 35°C—compared to Paraloid B44 and Incralac coatings—from 17 to 190 g m−2 day−1, respectively. The transmission rate parameters were also compared to the results of corrosion tests. Incralac was the most effective corrosion inhibitor, and the performance of the B44 was better than the B72, which is in good agreement with the transmission rate tests.

Softened Wood Treated by Deep Eutectic Solvents.

Due to its good physical properties, softened wood (SW) has been widely used in the fields of home furnishing, interior decoration, and construction, such as decorative panels, softened wood flooring, wooden bricks, and softened wood furniture. However, traditional methods of wood softening often fail to meet the requirements of enterprises for softening wood. Here, inspired by the research related to wood softening, we propose a method for directly preparing softened wood (SW) using a new type of “ionic liquid” eutectic solvent (DES) owing to its low cost, environmental friendliness, recyclability, and other advantages. To improve the adaptability of the study, a total of five types of DESs were designed and prepared, and by the microwave-assisted DES treatment of natural wood (NW), the purpose of softening wood was achieved. Then, we conducted a series of comparative analyses and performance tests on NW and SW, including microscopic images, chemical composition, color difference, and mechanical properties. The results show that the wood softened by DES has become a highly porous network structure, and partial lignin, hemicellulose, and cellulose have been removed. At the same time, different degrees of color change, lower hardness, excellent mechanical flexibility, and a compression rebound rate of up to about 90% are obtained. The above-mentioned various properties of SW provide great potential for its application in wood products.

Clinical impact of 18F-FDG-PET among memory clinic patients with uncertain diagnosis

PurposeTo assess the clinical impact and incremental diagnostic value of 18F-fluorodeoxyglucose (FDG-PET) among memory clinic patients with uncertain diagnosis.MethodsThe study population consisted of 277 patients who, despite extensive baseline cognitive assessment, MRI, and CSF analyses, had an uncertain diagnosis of mild cognitive impairment (MCI) (n = 177) or dementia (n = 100). After baseline diagnosis, each patient underwent an FDG-PET, followed by a post-FDG-PET diagnosis formulation. We evaluated (i) the change in diagnosis (baseline vs. post-FDG-PET), (ii) the change in diagnostic accuracy when comparing each baseline and post-FDG-PET diagnosis to a long-term follow-up (3.6 ± 1.8 years) diagnosis used as reference, and (iii) comparative FDG-PET performance testing in MCI and dementia conditions.ResultsFDG-PET led to a change in diagnosis in 86 of 277 (31%) patients, in particular in 57 of 177 (32%) MCI and in 29 of 100 (29%) dementia patients. Diagnostic change was greater than two-fold in the sub-sample of cases with dementia “of unclear etiology” (change in diagnosis in 20 of 32 (63%) patients). In the dementia group, after results of FDG-PET, diagnostic accuracy improved from 77 to 90% in Alzheimer’s disease (AD) and from 85 to 94% in frontotemporal lobar degeneration (FTLD) patients (p < 0.01). FDG-PET performed better in dementia than in MCI (positive likelihood ratios >5 and < 5, respectively).ConclusionWithin a selected clinical population, FDG-PET has a significant clinical impact, both in early and differential diagnosis of uncertain dementia. FDG-PET provides significant incremental value to detect AD and FTLD over a clinical diagnosis of uncertain dementia.

FPGA Implementation of Homotopic Path Planning Method with Automatic Assignment of Repulsion Parameter

In recent times, autonomous robots have become more relevant, aiming not only to be an extension of mobility and human performance but also allowing them to independently solve specific problems such as finding free-collision paths within some defined environments. In order to achieve this, several techniques have been developed, like action-reaction algorithms, sampling-based algorithms, and deterministic algorithms such as the Homotopy Path Planning Method (HPPM). This work presents, for the first time, a complete deterministic collision-free path planning scheme implemented in FPGA, which is mounted on a Scribbler 2 robot from Parallax. Then, an automatic algorithm of the repulsion parameter for the HPPM method is presented, using as a reference the minimum distance between the center of each obstacle with respect to the homotopic ideal path; furthermore, an algorithm is proposed for discriminating dead-end routes and collision risk trajectories, which allows us to obtain a feasible free-collision path that takes into account the robot dimensions. Besides, comparative performance tests have been carried out against other path-finding methods from the low degrees of freedom (low DoF) and sampling-based planners. Our proposal exhibits path calculation times which are 5 to 10 times faster on FPGA implementation, compared to the other methods and 10 to 100 times faster on PC implementation also compared to the rest. Similar results are obtained with regards to memory consumption, namely 20 to 200 times lower on FPGA implementation and 10 to 100 times lower on PC implementation.