Refine
Department, Institute
- Institut für Sicherheitsforschung (ISF) (36) (remove)
Document Type
- Conference Object (18)
- Article (12)
- Doctoral Thesis (2)
- Part of a Book (1)
- Contribution to a Periodical (1)
- Patent (1)
- Report (1)
Year of publication
Language
- English (36) (remove)
Has Fulltext
- no (36) (remove)
Keywords
Entering the work envelope of an industrial robot can lead to severe injury from collisions with moving parts of the system. Conventional safety mechanisms therefore mostly restrict access to the robot using physical barriers such as walls and fences or non-contact protective devices including light curtains and laser scanners. As none of these mechanisms applies to human-robot-collaboration (HRC), a concept in which human and machine complement one another by working hand in hand, there is a rising need for safe and reliable detection of human body parts amidst background clutter. For this application camera-based systems are typically well suited. Still, safety concerns remain, owing to possible detection failures caused by environmental occlusion, extraneous light or other adverse imaging conditions. While ultrasonic proximity sensing can provide physical diversity to the system, it does not yet allow to reliably distinguish relevant objects from background objects.This work investigates a new approach to detecting relevant objects and human body parts based on acoustic holography. The approach is experimentally validated using a low-cost application-specific ultrasonic sensor system created from micro-electromechanical systems (MEMS). The presented results show that this system far outperforms conventional proximity sensors in terms of lateral imaging resolution and thus allows for more intelligent muting processes without compromising the safety of people working close to the robot. Based upon this work, a next step could be the development of a multimodal sensor systems to safeguard workers who collaborate with robots using the described ultrasonic sensor system.
This contribution investigates the application of established pansharpening algorithms for the fusion of hyperspectral images from Raman microspectroscopy and panchromatic images from conventional brightfield microscopy. Seven different methods based on multiresolution analysis and component substitution were applied and evaluated through visual assessment and quantitative quality measures at full and reduced resolution. The results indicate that, among the considered concepts, multiresolution methods are the more promising approaches for a physically and chemically meaningful fusion of the considered modalities. Here, pansharpening based on high-pass filtering led to the best results.
The freshness changes in poultry fillets during storage were studied using a portable fiber-optic Raman spectrometer. Poultry fillets with the same storage life (9 days) and expiry date were purchased from a local store and stored at 4 °C. Their Raman spectra were measured on a daily basis up to day 21 using a QE Pro-Raman spectrometer with a laser excitation wavelength of 785 nm. The complex spectra were analyzed using Principal Components Analysis (PCA), which resulted in a separation of the samples into three quality classes according to their freshness: fresh, semi-fresh, and spoiled. These classes were based on and similar to the information inferred from the product label on the packages of poultry fillets. The PCA loadings revealed a decrease in the protein content of the poultry meat during spoilage, an increase in the formation of free amino acids, an increase in oxidation of amino acid residues, and an increase in microbial growth on the surface of the poultry fillets, as well as revealing information about hydrophobic interaction around the aliphatic residues. Similar groupings (fresh, semi-fresh, and spoiled) were also obtained from the results of an Agglomerative Hierarchical Cluster Analysis (AHCA) of the first five principal components. The results allow the conclusion that the portable fiber-optic Raman spectrometer can be used as a reliable and fast method for real-time freshness evaluation of poultry during storage.
The detection of human skin in images is a very desirable feature for applications such as biometric face recognition, which is becoming more frequently used for, e.g., automated border or access control. However, distinguishing real skin from other materials based on imagery captured in the visual spectrum alone and in spite of varying skin types and lighting conditions can be dicult and unreliable. Therefore, spoofing attacks with facial disguises or masks are still a serious problem for state of the art face recognition algorithms. This dissertation presents a novel approach for reliable skin detection based on spectral remission properties in the short-wave infrared (SWIR) spectrum and proposes a cross-modal method that enhances existing solutions for face verification to ensure the authenticity of a face even in the presence of partial disguises or masks. Furthermore, it presents a reference design and the necessary building blocks for an active multispectral camera system that implements this approach, as well as an in-depth evaluation. The system acquires four-band multispectral images within T = 50ms. Using a machine-learning-based classifier, it achieves unprecedented skin detection accuracy, even in the presence of skin-like materials used for spoofing attacks. Paired with a commercial face recognition software, the system successfully rejected all evaluated attempts to counterfeit a foreign face.
A deployment of the Vehicle-2-Vehicle communication technology according to ETSI is in preparation in Europe. Currently, a policy for a necessary Public Key Infrastructure to enrol cryptographic keys and certificates for vehicles and infrastructure component is in discussion to enable an interoperable Vehicle-2-Vehicle communication. Vehicle-2-Vehicle communication means that vehicles periodically send Cooperative Awareness Messages. These messages contain the current geographic position, driving direction, speed, acceleration, and the current time of a vehicle. To protect privacy (location privacy, “speed privacy”) of vehicles and drivers ETSI provides a specific pseudonym concept. We show that the Vehicle-2-Vehicle communication can be misused by an attacker to plot a trace of sequent Cooperative Awareness Messages and to link this trace to a specific vehicle. Such a trace is non-disputable due to the cryptographic signing of the messages. So, the periodically sending of Cooperative Awareness Messages causes privacy problems even if the pseudonym concept is applied.
The study aimed to detect volatile organic compounds (VOCs) during spoilage of chicken breast filets under modified atmosphere packaging (MAP, (70% O2; 30% CO2)). Storage tests were conducted at 6 °C in a household refrigerator. Measurements were made using untreated chicken breast filets and using filets inoculated with either Pseudomonas fluorescens or Escherichia coli bacteria. The gas space above the sample was adsorbed once a day on Tenax® TA and analyzed using thermal desorption-gas chromatography-mass spectrometry (TD-GC/MS). During storage, 60 volatile organic compounds of hydrocarbons, alcohols, aldehydes, ketones, esters, ethers, and sulfur-containing compounds were detected. It was shown that the presence of most hydrocarbons and aldehydes declined during storage time, whereas most of the alcohols, ketones, sulfur-containing compounds, esters, and ethers increased. Some of these detected VOCs could act as indicators to describe the freshness loss of the product. The best spoilage markers for spoiled chicken breast filets under MAP were 2-methyl-1-propanol, 2-methyl-1-butanol, 3-methyl-1-butanol, 3-hydroxy-2-butanone, ethyl acetate, 2-butanone, and sulfur-containing compounds.
A deployment of the Vehicle-to-Vehicle communication technology according to ETSI is in preparation in Europe. Currently, a Public Key Infrastructure policy for Intelligent Transport Systems in Europe is in discussion to enable V2V communication. This policy set aside two classes of keys and certificates for ITS vehicle stations: long term authentication keys and pseudonymous keys and certificates. We show that from our point of view the periodic sent Cooperative Awareness Messages with extensive data have technical limitations and together with the pseudonym concept cause privacy problems.
Recent studies point out that spoofing attacks using facial masks still are a severe problem for current biometric face recognition (FR) systems. As such systems are becoming more frequently used, for example, for automated border crossing or access control to critical infrastructure, advanced anti-spoofing techniques are necessary to counter these attacks. This work presents a novel, cross-modal approach that enhances existing solutions for face verification and uses multispectral short wave infrared (SWIR) imaging to ensure the authenticity of a face even in the presence of partial disguises and masks. It is evaluated on a dataset containing 137 subjects and a variety of spoofing attacks. Using a commercial FR system, it successfully rejects all attempts to counterfeit a foreign face with a false acceptance rate FARcf = 0% and most attempts to disguise the own identity with FARdg = 1% at a false rejection rate of FRR < 5% using SWIR images for verification.
Persons entering the working range of industrial robots are exposed to a high risk of collision with moving parts of the system, potentially causing severe injuries. Conventional systems, which restrict the access to this area, range from walls and fences to light barriers and other vision based protective devices (VBPD). None of these systems allow to distinguish between humans and workpieces in a safe and reliable manner. In this work, a new approach is investigated, which uses an active near-infrared (NIR) camera system with advanced capabilities of skin detection to distinguish humans from workpieces based on characteristic spectral signatures. This approach allows to implement more intelligent muting processes and at the same time increases the safety of persons working close to the robots. The conceptual integration of such a camera system into a VBPD and the enhancement of person detection methods through skin detection are described and evaluated in this paper. Based upon this work, next steps could be the development of multimodal sensor systems to safeguard working ranges of collaborating robots using the described camera system.
The proper use of protective hoods on panel saws should reliably prevent severe injuries from (hand) contact with the blade or material kickbacks. It also should minimize long-term lung damages from fine-particle pollution. To achieve both purposes the hood must be adjusted properly by the operator for each workpiece to fit its height. After a work process is finished, the hood must be lowered down completely to the bench. Unfortunately, in practice the protective hood is fixed at a high position for most of the work time and herein loses its safety features. A system for an automatic height adjustment of the hood would increase comfort and safety. If the system can distinguish between workpieces and skin reliably, it furthermore will reduce occupational hazards for panel saw users. A functional demonstrator of such a system has been designed and implemented to show the feasibility of this approach. A specific optical sensor system is used to observe a point on the extended cut axis in front of the blade. The sensor determines the surface material reliably and measures the distance to the workpiece surface simultaneously. If the distance changes because of a workpiece fed to the machine, the control unit will set the motor-adjusted hood to the correct height. If the sensor detects skin, the hood will not be moved. In addition a camera observes the area under the hood. If there are no workpieces or offcuts left under the hood, it will be lowered back to the default position.
The device (10) has a handrail (18) provided with an optical contactless monitoring device formed as an active sensor system, where the monitoring device is arranged in a region of a guide (14) of the handrail at a front base (16) of an escalator (12) or a moving pavement. The monitoring device has two transmission paths (28, 30) with wavelength bands that are different from each other, where one of the paths includes the handrail. Ratio or difference between signals of the paths is used for recognizing foreign bodies e.g. hands of adults and children.
Artificial waters containing the xenobiotics atrazine, bisphenol A and chlorendic acid were treated by use of micro-disinfection apparatus, based on electrochemical ozone production. The design and working principle, as well as the applicability of the apparatus for the degradation of the target compounds is presented. The initial concentrations of the analytes were chosen to be in the mg L−1 order. Degradation and transformation of the analytes was determined via LC-MS, UV/Vis, and IC. Bisphenol A was degraded completely within short ozonation times, but complete mineralization could not be achieved. Ion chromatography indicated formic and oxalic acid to be transformation products. For atrazine a degradation of 96% could be achieved within 3 h. Intermediate transformation products, like desethylatrazine, desisopropylatrazine, and desethyl-desisopropylatrazine, are formed and further degraded to formic acid and chloride. Chlorendic acid was degraded by up to 40% of the initial concentration. Analyses by UV/Vis and IC again showed formic acid, chloride, and also chlorate to be transformation products.
At previous SIAS conferences, we presented a novel opto-electronic safety sensor system for skin detection at circular saws jointly developed with the Institute for Occupational Safety and Health of the German Social Accident Insurance (IFA). This work now presents the development results of our consecutive research on a prototype of a sensor system for more general production machine applications including robot workplaces. The system uses offthe shelf LEDs and photodiodes in combination with dedicated optics and a microcontroller system to implement a so-called spectral light curtain.
Microcontroller-based sensor systems offer great opportunities for the implementation of safety features for potentially dangerous machinery. However, in general they are difficult to assess with regard to their reliability and failure rate. This paper describes the safety assessment of hardware and software of a new and innovative sensor system. The hardware is assessed by standardized methods according to norm EN ISO 13849-1, while the use of model checking is presented as an approach to solve the problem of validating the software.
In this paper, we introduce an optical sensor system, which is integrated into an industrial push-button. The sensor allows to classify the type of material that is in contact with the button when pressed into different material categories on the basis of the material's so called "spectral signature". An approach for a safety sensor system at circular table saws on the same base has been introduced previously on SIAS-2007. This contactless working sensor is able to distinguish reliably between skin, textiles, leather and various other kinds of materials. A typical application for this intelligent push-button is the use at possibly dangerous machines, whose operating instructions include either the prohibition or the obligation to wear gloves during the work at the machine. An exemple of machines at which no gloves are allowed are pillar drilling machines, because of the risk of getting caught in the drill chuck and being turned in by the machine. In many cases this causes very serious hand injuries. Depending on the application needs, the sensor system integrated into the push-button can be configured flexibly by software to prevent the operator from accidentally starting a machine with or without gloves, which can decrease the risk of severe accidents significantly. Especially two-hand controls are incentive to manipulation for easier handling. By equipping both push-buttons of a two-hand control with material classification properties, the user is forced to operate the controls with his bare fingers. That limitation disallows the manipulation of a two-hand control by a simple rodding device.
The use of manually fed machines (e.g. table saws) bares risks of injury that are clearly above the average level of other high risk workplaces.
The wide use of such machines causes severe problems for occupational safety and implies high costs for medical treatments and accident annuities.
This thesis presents a new concept of a multispectral sensor to monitor an area in front of a danger zone to detect the user’s limbs and trigger safeguarding measures to prevent an accident in time.
The sensor concept realizes a contact-free material classification, which comprises the development of a system design and specific safety requirements with respect to international safety standards.
Furthermore, a prototypical implementation using four wavebands, which were determined for skin detection through an analysis of reflectance spectra acquired specifically for this purpose, was built.
This paper presents recent research on an active multispectral scanning sensor capable of classifying an object's surface material in order to distinguish between different kinds of materials and human skin. The sensor itself has already been presented in previous work and can be used in conjunction with safeguarding equipment at manually-fed machines or robot workplaces, for example. This work shows how an extended sensor system with advanced material classifiers can be used to provide additional value by distinguishing different materials of work pieces in order to suggest different tools or parameters for the machine (e.g. the use of a different saw blade or rotation speed at table saws). Additionally, a first implementation and evaluation of an active multispectral camera system addressing new safety applications is described. Both approaches intend to increase the productivity and the user's acceptance of the sensor technology.
Safety applications require fast, precise and highly reliable sensors at low costs. This paper presents signal processing methods for an active multispectral optical point sensor instrumentation for which a first technical implementation exists. Due to the very demanding requirements for safeguarding equipment, these processing methods are targeted to run on a small embedded system with a guaranteed reaction time T < 2 ms and a sufficiently low failure rate according to applicable safety standards, e.g., ISO-13849. The proposed data processing concept includes a novel technique for distance-aided fusion of multispectral data in order to compensate for displacement-related alteration of the measured signal. The distance measuring is based on triangulation with precise results even for low-resolution detectors, thus strengthening the practical applicability. Furthermore, standard components, such as support vector machines (SVMs), are used for reliable material classification. All methods have been evaluated for variants of the underlying sensor principle. Therefore, the results of the evaluation are independent of any specific hardware.
Commercial light curtains use a technique known as muting to differentiate between work pieces and other objects (e.g., human limbs) based on precise model knowledge of the process. At manually fed machinery (e.g., bench saws), such precise models cannot be derived due to the way the machinery is used. This paper presents a multispectral scanning sensor to classify an object's surface material as a new approach for the problem. The system is meant to detect the presence of limbs and therefore optimized for human skin detection. Evaluation on a test set of skin and (wet) wood samples showed a sufficiently high reliability with respect to safety standards.
The FIVIS simulator system addresses the classical visual and acoustical cues as well as vestibular and further physiological cues. Sensory feedback from skin, muscles, and joints are integrated within this virtual reality visualization environment. By doing this it allows for simulating otherwise dangerous traffic situations in a controlled laboratory environment. The system has been successfully applied for road safety education applications of school children. In further research studies it is applied to perform multimedia perception experiments. It has been shown, that visual cues dominate by far the perception of visual depth in the majority of applications but the quality of depth perception might depend on the availability of other sensory information. This however, needs to be investigated in more detail in the future.
Safety and security applications often need to gather data from distributed locations and a multitude of instruments and sensors. We have developed a gas sensing platform that communicates via a wireless sensor network based on IEEE 802.15.4 and/or Ethernet. The data form this network is aggregated via a central server that feeds its information over TCP/IP into subsequent data fusion software.
This work addresses the problem of measuring psychological strain in humans by the use of physiological data. The aim of the work is the research, development and evaluation of a measurement system for the acquisition of such data from humans and the differentiation of psychological and physical strain with the help of machine learning algorithms. The developed system records and analyzes the ECG, the EMG, as well as the skin conductance, and combines these physiological parameters with the subject’s physical activity. The main purpose of this measurement system is to assess both types of strain in employees at their workplaces.
Several hundred accidents involving the use of circular saws and resulting in injury, to hands or fingers occur each year in Germany.
In the presented project, new approaches for the prevention of hand injuries and for the contactless detection of fingers are being investigated for comprehensive protection on circular saws. The basic principles can be applied to other machines with manual loading and/or unloading. This paper describes several principles to distinct human skin and wood and a safety guard that prevents touching the rotating blade. In a first approach a reliable protective device with functional diversity has been developed using a passive infrared sensor in combination with a capacitive field sensor. Second the distinction between skin and wood or other material is done by dedicated kind of spectral analysis in the near infrared region. With a kind of light curtain the intrusion into the dangerous zone near the blade can be prevented.
The safety guard protects the operator’s hand within 50 ms. The forces of the protective system peak at no more than 120 N. We are presenting a complete strategy for such different tasks as cutting wedges, stopped cutting and hidden cutting, which have a very high odds ratio.
In the presented project, new approaches for the prevention of hand movements leading to hazards and for non-contact detection of fingers are intended to permit comprehensive and economical protection on circular saws. The basic principles may also be applied to other machines with manual loading and/or unloading. Two new detection principles are explained. The first is the distinction between skin and wood or other material by spectral analysis in the near infrared region. Using LED and photodiodes it is possible to detect fingers and hands reliable. With a kind of light curtain the intrusion into the dangerous zone near the blade can be prevented. The second principle is video image processing to detect persons, arms and fingers. In the first stage of development the detection of upper limb extremities within a defined hazard area by means of a computer based video image analysis is investigated.
