Twirre is a new architecture for mini-UAV platforms designed for autonomous flight in both GPS-enabled and GPS-deprived applications. The architecture consists of low-cost hardware and software components. High-level control software enables autonomous operation. Exchanging or upgrading hardware components is straightforward and the architecture is an excellent starting point for building low-cost autonomous mini-UAVs for a variety of applications. Experiments with an implementation of the architecture are in development, and preliminary results demonstrate accurate indoor navigation
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Twirre V2 is the evolution of an architecture for mini-UAV platforms which allows automated operation in both GPS-enabled and GPSdeprived applications. This second version separates mission logic, sensor data processing and high-level control, which results in reusable software components for multiple applications. The concept of Local Positioning System (LPS) is introduced, which, using sensor fusion, would aid or automate the flying process like GPS currently does. For this, new sensors are added to the architecture and a generic sensor interface together with missions for landing and following a line have been implemented. V2 introduces a software modular design and new hardware has been coupled, showing its extensibility and adaptability
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Several studies have suggested that precision livestock farming (PLF) is a useful tool foranimal welfare management and assessment. Location, posture and movement of an individual are key elements in identifying the animal and recording its behaviour. Currently, multiple technologies are available for automated monitoring of the location of individual animals, ranging from Global Navigation Satellite Systems (GNSS) to ultra-wideband (UWB), RFID, wireless sensor networks (WSN) and even computer vision. These techniques and developments all yield potential to manage and assess animal welfare, but also have their constraints, such as range and accuracy. Combining sensors such as accelerometers with any location determining technique into a sensor fusion systemcan give more detailed information on the individual cow, achieving an even more reliable and accurate indication of animal welfare. We conclude that location systems are a promising approach to determining animal welfare, especially when applied in conjunction with additional sensors, but additional research focused on the use of technology in animal welfare monitoring is needed.
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This paper describes the concept of a new algorithm to control an Unmanned Aerial System (UAS) for accurate autonomous indoor flight. Inside a greenhouse, Global Positioning System (GPS) signals are not reliable and not accurate enough. As an alternative, Ultra Wide Band (UWB) is used for localization. The noise is compensated by combining the UWB with the delta position signal from a novel optical flow algorithm through a Kalman Filter (KF). The end result is an accurate and stable position signal with low noise and low drift.
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Localization is a crucial skill in mobile robotics because the robot needs to make reasonable navigation decisions to complete its mission. Many approaches exist to implement localization, but artificial intelligence can be an interesting alternative to traditional localization techniques based on model calculations. This work proposes a machine learning approach to solve the localization problem in the RobotAtFactory 4.0 competition. The idea is to obtain the relative pose of an onboard camera with respect to fiducial markers (ArUcos) and then estimate the robot pose with machine learning. The approaches were validated in a simulation. Several algorithms were tested, and the best results were obtained by using Random Forest Regressor, with an error on the millimeter scale. The proposed solution presents results as high as the analytical approach for solving the localization problem in the RobotAtFactory 4.0 scenario, with the advantage of not requiring explicit knowledge of the exact positions of the fiducial markers, as in the analytical approach.
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On April 12th 2019, researchers, students and consortia gathered at the World Horti Centre for an update on the overall status of the HiPerGreen project. The day consisted of presentations from a variety of the HiPerGreen students, staff and guest speakers. There were a variety of exciting updates from the technological and biological realms of the project, as well as an insightful presentation from Deliflor’s Geert Van Geest on Deliflor and their interests in imaging of chrysanthemums. Several new pieces of technology have arisen from the HiPerGreen project. The first being a rail-based imaging system capable of traversing the greenhouse using the heating pipes commonly found in Dutch greenhouses. The drone landing dock has also taken great steps forward and finally, HiPerGreen has partnered with drone manufacture Avular, a company working on the world’s first ‘ultra-wide band’ localized indoor drone. From a biological standpoint significant progress has been made regarding long-term plant monitoring with a focus on reducing fusarium occurrence in the crop. Students are working in climate chambers to model the symptoms of fusarium infection in orchids. Students are also working at Deliflor using the railsystem to measure uniformity in chrysanthemum test crops. Research with the multispectral camera continued and the team hopes to integrate the imaging into mass plant monitoring. The sympoium was concluded with a drink.
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In mobile robotics, LASER scanners have a wide spectrum of indoor and outdoor applications, both in structured and unstructured environments, due to their accuracy and precision. Most works that use this sensor have their own data representation and their own case-specific modeling strategies, and no common formalism is adopted. To address this issue, this manuscript presents an analytical approach for the identification and localization of objects using 2D LiDARs. Our main contribution lies in formally defining LASER sensor measurements and their representation, the identification of objects, their main properties, and their location in a scene. We validate our proposal with experiments in generic semi-structured environments common in autonomous navigation, and we demonstrate its feasibility in multiple object detection and identification, strictly following its analytical representation. Finally, our proposal further encourages and facilitates the design, modeling, and implementation of other applications that use LASER scanners as a distance sensor.
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Humidification is not a common procedure in many buildings in the Netherlands. An exception are buildings used for healthcare, especially hospitals. There, e.g. in operating theatres, relative humidity (RH) generally is controlled stringently at levels around 50%. From an energy point-of-view humidification is an energy-intensive activity. Currently, more than 10% of the total energy used in healthcare buildings is spent on humidification. The basis for an RH of around 50%, however, is not clear. Therefore, we pursued a scoping review to find evidence for specific RH thresholds in such facilities. In addition, an inventory was made of the current practice in the Netherlands. After analyzing the title and abstracts, the remaining references were read by two persons and scored on several topics. Guidelines and current practice were analyzed by referring to existing (inter)national guidelines and standards, and by contacting experts from Dutch hospitals through a survey and semi-structured interviews. Outcomes from the literature review were grouped into four different topics: 1) micro-organisms and viruses, 2) medical devices, 3) human physiology and 4) perception. No scientific evidence was found for the currently generally applied RH set-point of ~50%. Some studies suggest a minimum RH of 30% but the evidence is weak, with exception of medical devices if specifications require it. A lack of research that addresses more long-term exposure (a couple of days) and includes frail subjects, is noted. It was found that RH requirements are strictly followed in all hospitals consulted, some only focusing on the hot zones, but in many cases extended to the whole hospital. Steam humidification is mostly applied for hygienic reasons. but is quite energy-intensive. The conclusion t is that there is no solid evidence to support the RH-setpoints as currently applied in the Netherlands. It merely appears a code of practice. Therefore, there appears room for quick and significant energy savings, and CO2 emission reductions, when considering control at lower RH values or refraining from humidification at all, while still fulfilling the indoor environment requirements and not negatively influencing the health risk. This outcome can be applied directly in current practice with the available techniques.
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Discussions about the importance of the built environment for healthcare delivery extend at least as far back as Hippocrates 1 (400 BC). The iconic Florence Nightingale (1859) also strongly believed in the influence the indoor environment has on the progress of disease and recovery. Today, the role of the built environment in the healing process is of growing interest to healthcare providers, environmental psychologists, consultants, and architects. Although there is a mounting evidence 1 linking healthcare environments to health outcomes, because of the varying quality of that evidence, there has also been a lack of clarity around what can and cannot be achieved through design. Given the ageing of society and the ever increasing numbers of persons with dementia in the Western World, the need for detailed knowledge about aged care environments has also become increasingly important. The mental and physical health state of these persons is extremely fragile and their needs demand careful consideration. Although environmental interventions constitute only a fraction of what is needed for people with dementia to remain as independent as possible, there is now sufficient evidence (2, 3) to argue they can be used as a first-line treatment, rather than beginning with farmalogical interventions.
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Travelling independently in an urban environment is challenging for people with a visual impairment (PVI). Current Wayfinding-apps lack detailed environmental information and are often not fully accessible. With the aim to design a wayfinding solution that facilitates independent travel and incorporates PVI needs and wishes, we deployed a cocreation design approach with PVI and professionals as co-creators. Our combination of different co-creation techniques and iterative prototyping expands the related research on wayfinding solutions and allowed us to zoom-in on specific features. Our approach started with a userrequirements analysis through selfexperience sessions, observations and focus groups. This was followed by iterative prototyping with user evaluations in controlled indoor and outdoor environments. Over a period of two years we created an accessible wayfinding solution in co-creation with 31 PVI and 19 professionals. This resulted in an optimized accessible interface, a personalized route, personalized wayfinding instructions and detailed orientation and environmental information. Lessons learned for co- design with PVI included setting up an accessible workshop environment, applying diverse evaluation methods and involving reoccurring participants.
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