Search Results (46)

A backyard cat with symptoms of otitis was transferred to a veterinary clinic in Central Greece. A sample was obtained and P. aeruginosa was isolated. The strain exhibited an extensively drug-resistant (XDR) profile, as it was non-susceptible to all tested agents except colistin. DNA extraction and whole-genome sequencing (WGS) were performed using a robotic extractor and Ion Torrent technology, respectively. The genome was assembled and screened for resistance and virulence determinants. The isolate belonged to the high-risk clone ST308 with a total of 67 antibiotic resistance genes (ARGs) and 221 virulence factor-related genes being identified. No plasmids were detected. The metallo-beta-lactamase (MBL) bla_NDM-1 gene and 46 efflux pumps were included in the strain’s resistome. Both ARGs conferring tolerance to disinfecting agents and biofilm-related genes were identified, associated with the ability of this clone to adapt and persist in healthcare facilities. This case highlights the risk of relevant bacterial clones spreading in the community and even being transmitted to companion animals, causing challenging opportunistic infections to susceptible individuals, while others may become carriers, further spreading the clones to their owners, other animals and the environment. Full article

This study delves into the mapping method for the navigation system of a chicken coop disinfection robot. It systematically analyzes the problems of insufficient effective particle count, high particle repetition rate in environmental map information, and penetration phenomenon in traditional SLAM laser point cloud mapping technology in chicken coop environments containing multiple layers of chicken cages. To address these issues, this paper proposes an optimized mapping method based on an improved ICP algorithm, significantly improving the laser point clouds’ registration performance. At the same time, by limiting the sampling of environmental map information particles within a specific range and optimizing the screening based on the predicted distribution of particle poses and the matching degree of the map, the diversity of particles and the accuracy of map information have been effectively improved. The field experiment results show that the maximum error of this method on the chicken coop environment map does not exceed 3.5 cm. The environmental characteristics of the chicken coop are maximally preserved, which verifies the effectiveness and robustness of this method and provides a scientific basis for the mapping method of the livestock and poultry breeding robot navigation system. Full article

As the epidemic affected everyone across the world, the solution to the epidemic was developed globally. Many applications adopt Internet of Things (IoT) technology to detect epidemics, and effective monitoring systems are developed to monitor air pollution, personal transmission, early detection of serious cases, and remote assessment. However, care facilities in an aging society require effective disinfection and sterilization to prevent viral transmission. We integrated the interactive and real-time features of the Internet of Things (IoT) to design and build an intelligent self-propelled sterilization robot for sterilization. Intelligent sterilization and disinfection planning and task allocation mechanisms were designed for sterilization in clinics. For healthcare facilities, the developed robot can reduce the burden on healthcare professionals, help to manage the disinfection and sterilization process, and ensure patient safety. At the same time, robots promote the development of epidemic prevention industries and prepares for future attacks from harmful air pollutants or new infections. Full article

In the post-COVID era, international business and tourism are quickly recovering from the global lockdown, with people and products traveling faster at higher frequency. This boosts the economy while facilitating the spread of pathogens, causing waves of COVID aftershock with new variants like Omicron XBB. Hence, continuous disinfection of our living environments becomes our first priority. Autonomous disinfection robots provide an efficient solution to this issue. Compared to human cleaners, disinfection robots are able to operate tirelessly in harsh environments without increasing the risk of cross-infection. In this paper, we propose the design of a new generation of the Smart Cleaner disinfection robot, which is equipped with both an Ultraviolet-C (UVC) light tower and a hydrogen peroxide (HP) aerosol dispenser. The safety of an autonomous disinfection robot has been a persistent problem, especially when they work in complex environments. To tackle this problem, Hamilton–Jacobi (HJ) reachability is adopted to construct a safety filter for motion control, which guarantees that the disinfection path taken by the robot is collision-free without severely compromising the optimality of control actions. The effectiveness of the developed robot has been demonstrated by conducting extensive experimental studies. Full article

Background: The purpose of this work was to demonstrate the ozone efficacy for disinfection of the PHARMODUCT^® automatic dispensing system for antineoplastic preparation, as a guarantee of a higher grade of cleanliness. While the use of ozone gas disinfection is almost consolidated in food and water treatment, there is a lack of scientific data in the pharmaceutical field. The scope of this study was to demonstrate the ozone efficacy for disinfection of the PHARMODUCT^® automatic dispensing system, before starting the antineoplastic preparation, in order to ensure a high degree of cleanliness and, at the same time, to define a biodecontamination procedure that could also be translatable to other automated compounding systems on the market. Methods: Ozone efficacy was determined by calculating the difference (pre-exposure–post-exposure) in CFU counts on the plate. A group of four different ATCC-selected microbial strains were tested using two distinct cycles. The first one was evaluated with an ozone gas concentration of 40 ppm for 40 min; the second cycle increased the concentration to 60 ppm for the same duration. Results: Results showed that exposure to 40 ppm ozone gas led to a 4-log reduction of all tested ATCC strains. In contrast, exposure to 60 ppm ensured a 6-log reduction. Conclusions: The ozone disinfection process, applied to the PHARMODUCT^® system, provides a superior grade of cleanliness compared to the manual disinfection procedure, thus offering insight beyond the current anti-inflammatory and analgesic application of ozone therapy in the medical field. Full article

Current disinfection robots either have a bulky design or cannot operate in multiple configurations, therefore being unable to disinfect the hard-to-reach areas, which leads to low efficiency of the disinfection process. A solution for this problem would be to use disinfection robots with folding mechanisms which can operate in different configurations based on the area type that needs to be disinfected. This paper presents the feasibility study of the 7-PR(RRRR)RP seven-bar linkage used for a disinfection robot with folding mechanism. First, the structure’s parameters were computed with a synthesis method by developing the inequalities system in order to avoid the singularities positions of the mechanism. This initial method took into consideration different values of the design coefficient p (which indicates the two possible designs of the selected linkage) and an arbitrary value of the coefficient k > 1, which was imposed in order to substitute the resulting inequalities system with an equation system. However, applying this method does not ensure that the optimal 7-PR(RRRR)RP seven-bar linkage structure for the design of a medical disinfection robot is obtained. Furthermore, an optimized synthesis method was applied, which took into consideration the ratio between the total height of the mechanism and its total size. The parameters of the seven-bar linkage were computed for multiple values of the design coefficient p ∈ [1.1; 2] and multiple values of the coefficient k ∈ (0; 2], while a target function was implemented in order to identify the mechanism with the highest height range and the lowest size, which is considered to be the optimal structure for the design of a medical disinfection robot with a folding mechanism. The accuracy and the reliability of the results are furthermore strengthened by a performance analysis between the optimal indicated structure from the optimized synthesis method and other 7-PR(RRRR)RP seven-bar linkage structures, which were computed with different values of the parameters. Full article

Some large social environments are expected to use Covered Path Planning (CPP) methods to handle daily tasks such as cleaning and disinfection. These environments are usually large in scale, chaotic in structure, and contain many obstacles. The proposed method is based on the improved SCAN-STC (Spanning Tree Coverage) method and significantly reduces the solution time by optimizing the backtracking module of the algorithm. The proposed method innovatively introduces the concept of optimal backtracking points to sacrifice the spatial complexity of the algorithm to reduce its computational complexity. The necessity of backtracking in such environments is proved to illustrate the generalization ability of the method. Finally, based on secondary coding, the STC solution is explicitly expressed as a continuous and cuttable global path, which can be generalized to Multi-robot Covered Path Planning (MCPP) to avoid the path conflict problem in the multi-robot system, and the paths assigned to each robot have good balance. The method of this study is proven to be effective through simulations in various random environments and a real environment example. Compared with the advanced methods, the computational time is reduced by 82.47%. Full article

The COVID-19 pandemic highlighted the urgent need for effective surface disinfection solutions, which has led to the use of mobile robots equipped with ultraviolet (UVC) lamps as a promising technology. This study aims to optimize the navigation of differential mobile robots equipped with UVC lamps to ensure maximum efficiency in disinfecting complex environments. Bio-inspired metaheuristic algorithms such as the gazelle optimization algorithm, whale optimization algorithm, bat optimization algorithm, and particle swarm optimization are applied. These algorithms mimic behaviors of biological beings such as the evasive maneuvers of gazelles, the spiral hunting patterns of whales, the echolocation of bats, and the collective behavior of flocks of birds or schools of fish to optimize the robot’s trajectory. The optimization process adjusts the robot’s coordinates and the time it takes to stops at key points to ensure complete disinfection coverage and minimize the risk of excessive UVC exposure. Experimental results show that the proposed algorithms effectively adapt the robot’s trajectory to various environments, avoiding obstacles and providing sufficient UVC radiation exposure to deactivate target microorganisms. This approach demonstrates the flexibility and robustness of these solutions, with potential applications extending beyond COVID-19 to other pathogens such as influenza or bacterial contaminants, by tuning the algorithm parameters. The results highlight the potential of bio-inspired metaheuristic algorithms to improve automatic disinfection and achieve safer and healthier environments. Full article

The economic friction and political conflicts between some countries and regions have made multinational corporations increasingly focus on the reliability and credibility of manufacturing supply chains. In view of the impact of poor manufacturing entity reliability and service reputation on the new-era manufacturing industry, the time-varying reliability and time-varying credibility of cloud manufacturing (CMfg) services were studied from the perspective of combining nature and society. Taking time-varying reliability, time-varying credibility, composition complexity, composition synergy, execution time, and execution cost as objective functions, a new six-dimension comprehensive evaluation model of service quality was constructed. To solve the optimization problem, this study proposes an improved chaos sparrow search algorithm (ICSSA), where the Bernoulli chaotic mapping formula was introduced to improve the basic sparrow search algorithm (BSSA), and the position calculation formulas of the explorer sparrow and the scouter sparrow were enhanced. The Bernoulli chaotic operator changed the symmetry of the BSSA, increased the uncertainty and randomness of the explorer sparrow position in the new algorithm, and affected the position update and movement strategies of the follower and scouter sparrows. The asymmetric chaotic characteristic brought better global search ability and optimization performance to the ICSSA. The comprehensive performance of the service composition (SvcComp) scheme was evaluated by calculating weighted relative deviation based on six evaluation elements. The WFG and DTLZ series test functions were selected, and the inverse generation distance (IGD) index and hyper volume (HV) index were used to compare and evaluate the convergence and diversity of the ICSSA, BSSA, PSO, SGA, and NSGA-III algorithms through simulation analysis experiments. The test results indicated that the ICSSA outperforms the BSSA, PSO, SGA, and NSGA-III in the vast majority of testing issues. Finally, taking disinfection robot manufacturing tasks as an example, the effectiveness of the proposed CMfg SvcComp optimization model and the ICSSA were verified. The case study results showed that the proposed ICSSA had faster convergence speed and better comprehensive performance for the CMfg SvcComp optimization problem compared with the BSSA, PSO, SGA, and NSGA-III. Full article

Ultraviolet (UV) radiation has been widely utilized as a disinfection strategy to effectively eliminate various pathogens. The disinfection task achieves complete coverage of object surfaces by planning the motion trajectory of autonomous mobile robots and the UVC irradiation strategy. This introduces an additional layer of complexity to path planning, as every point on the surface of the object must receive a certain dose of irradiation. Nevertheless, the considerable dosage required for virus inactivation often leads to substantial energy consumption and dose redundancy in disinfection tasks, presenting challenges for the implementation of robots in large-scale environments. Optimizing energy consumption of light sources has become a primary concern in disinfection planning, particularly in large-scale settings. Addressing the inefficiencies associated with dosage redundancy, this study proposes a dose coverage planning framework, utilizing MOPSO to solve the multi-objective optimization model for planning UVC dose coverage. Diverging from conventional path planning methodologies, our approach prioritizes the intrinsic characteristics of dose accumulation, integrating a UVC light efficiency factor to mitigate dose redundancy with the aim of reducing energy expenditure and enhancing the efficiency of robotic disinfection. Empirical trials conducted with autonomous disinfecting robots in real-world settings have corroborated the efficacy of this model in deactivating viruses. Full article

The traditional aviary decontamination process involves farmers applying pesticides to the aviary’s ground. These agricultural defenses are easily dispersed in the air, making the farmers susceptible to chronic diseases related to recurrent exposure. Industry 5.0 raises new pillars of research and innovation in transitioning to more sustainable, human-centric, and resilient companies. Based on these concepts, this paper presents a new aviary decontamination process that uses IoT and a robotic platform coupled with ozonizer (O₃) and ultraviolet light (UVL). These clean technologies can successfully decontaminate poultry farms against pathogenic microorganisms, insects, and mites. Also, they can degrade toxic compounds used to control living organisms. This new decontamination process uses physicochemical information from the poultry litter through sensors installed in the environment, which allows accurate and safe disinfection. Different experimental tests were conducted to construct the system. First, tests related to measuring soil moisture, temperature, and pH were carried out, establishing the range of use and the confidence interval of the measurements. The robot’s navigation uses a back-and-forth motion that parallels the aviary’s longest side because it reduces the number of turns, reducing energy consumption. This task becomes more accessible because of the aviaries’ standardized geometry. Furthermore, the prototype was tested in a real aviary to confirm the innovation, safety, and effectiveness of the proposal. Tests have shown that the UV + ozone combination is sufficient to disinfect this environment. Full article

In this paper, an improved APF-GFARRT* (artificial potential field-guided fuzzy adaptive rapidly exploring random trees) algorithm based on APF (artificial potential field) guided sampling and fuzzy adaptive expansion is proposed to solve the problems of weak orientation and low search success rate when randomly expanding nodes using the RRT (rapidly exploring random trees) algorithm for disinfecting robots in the dense environment of disinfection operation. Considering the inherent randomness of tree growth in the RRT* algorithm, a combination of APF with RRT* is introduced to enhance the purposefulness of the sampling process. In addition, in the context of RRT* facing dense and restricted environments such as narrow passages, adaptive step-size adjustment is implemented using fuzzy control. It accelerates the algorithm’s convergence and improves search efficiency in a specific area. The proposed algorithm is validated and analyzed in a specialized environment designed in MATLAB, and comparisons are made with existing path planning algorithms, including RRT, RRT*, and APF-RRT*. Experimental results show the excellent exploration speed of the improved algorithm, reducing the average initial path search time by about 46.52% compared to the other three algorithms. In addition, the improved algorithm exhibits faster convergence, significantly reducing the average iteration count and the average final path cost by about 10.01%. The algorithm’s enhanced adaptability in unique environments is particularly noteworthy, increasing the chances of successfully finding paths and generating more rational and smoother paths than other algorithms. Experimental results validate the proposed algorithm as a practical and feasible solution for similar problems. Full article

In the face of today’s ever-evolving global health landscape and ambient assisted living (AAL), marked by the persistent emergence of novel viruses and diseases that impact vulnerable categories and individual safety, the need for innovative disinfection solutions has surged to unprecedented levels. In pursuit of advancing the field of autonomous UV-C disinfection robotics, we conducted two comprehensive state-of-the-art analyses: the first one in the literature and the second one in existing commercial disinfection robots to identify current challenges. Of all of the challenges, we consider the most outstanding ones to be safeguarding humans and animals and understanding the surroundings while operating the disinfection process challenges that we will address in this article. While UV-C lamps have demonstrated their effectiveness in sterilizing air and surfaces, the field of autonomous UV-C disinfection robotics represents a critical domain that requires advancement, particularly in safeguarding the wellbeing of humans and animals during operation. Operating UV-C disinfection robots in close proximity to humans or animals introduces inherent risks, and existing disinfection robots often fall short in incorporating advanced safety systems. In response to these challenges, we propose the RoboCoV Cleaner—an indoor autonomous UV-C disinfection robot equipped with an advanced dual and redundant safety system. This novel approach incorporates multiple passive infrared (PIR) sensors and AI object detection on a 360-degree camera. Under our test, the dual-redundant system reached more than 90% when detecting humans with high accuracy using the AI system 99% up to 30 m away in a university hallway (different light conditions) combined with the PIR system (with lower accuracy). The PIR system was proved to be a redundant system for uninterrupted operation during communication challenges, ensuring continuous sensor information collection with a swift response time of 50 ms (image processing within 200 ms). It empowers the robot to detect and react to human presence, even under challenging conditions, such as when individuals wear masks, in complete darkness, under UV light, or in environments with blurred visual conditions. In our test, the detection system performed outstandingly well with up to 99% detection rate of humans. Beyond safety features, the RoboCoV Cleaner can identify objects in its surroundings. This capability empowers the robot to discern objects affected by UV-C light, enabling it to apply specialized rules for targeted disinfection. The proposed system exhibits a wide range of capabilities beyond its core purpose of disinfection, making it suitable for healthcare facilities, universities, conference venues, and hospitals. Its implementation has the ability to improve significantly human safety and protect people. By showcasing the RoboCoV Cleaner’s safety-first approach and adaptability, we aim to set a new benchmark for UV-C disinfection robots, promoting clean and secure environments while protecting vulnerable people, even in challenging scenarios. Full article

To address the common drawbacks of current disinfection robots, which include the potential for secondary environmental pollution, disinfection dead corners, and low efficiency, in this paper, an autonomous mobile combination disinfection system is proposed. The system utilizes ultraviolet (UV) radiation and a low-concentration hydrogen peroxide aerosol to kill pathogens. It comprises three parts: a human–computer interface, a mobile robot, and disinfection equipment. A disinfection process model with continuous and fixed-point modes was established, and the effective disinfection range, speed, and duration were quantitatively calculated. The developed prototype was tested on-site by a professional third-party testing agency. The experimental results demonstrated that the combination disinfection robot achieved a 92.95% disinfection rate of natural airborne bacteria in a room measuring 22 square meters with a height of 2.8 m in just 30 min. The disinfection efficiency is at least 25% higher compared to standalone UV lamp disinfection and also exhibits a noticeable improvement over standalone hydrogen peroxide aerosol disinfection. The system enables the environmentally friendly, rapid, efficient, and all-encompassing disinfection of natural airborne bacteria. Finally, various disinfection solutions and recommendations for different application scenarios and requirements are provided. Full article

In facing the outbreak of the pandemic, robots are highly appealing for their non-contact nature. Among them, we have selected the mobile robot manipulator to develop an autonomous system for pandemic prevention, as it possesses both mobility and manipulability. The robot was used as a platform for performing autonomous fever detection, medicine delivery, and environmental disinfection system for the fever station and isolation ward, which are the two primary units that deal with the pandemic in a hospital. The proposed novel algorithms aim to ensure both human safety and comfort by automating fever detection and recognizing medicine taking. Additionally, they address environmental disinfection by effectively covering blind spots. We conducted a series of experiments to evaluate their performance in a hospital-like setting, which was designed specifically for the testing of intelligent medical systems developed in our university. Quantitative assessment was administered to analyze how the introduction of the proposed autonomous system reduced the risk of infection, and feedback was also collected from participants through questionnaires. Full article