Browsing by Author "Oliveira, Andre Schneider"
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- ARENA—augmented reality to enhanced experimentation in smart warehousesPublication . Piardi, Luis; Kalempa, Vivian Cremer; Limeira, Marcelo A.; Oliveira, Andre Schneider; Leitão, PauloThe current industrial scenario demands advances that depend on expensive and sophisticated solutions. Augmented Reality (AR) can complement, with virtual elements, the real world. Faced with this features, an AR experience can meet the demand for prototype testing and new solutions, predicting problems and failures that may only exist in real situations. This work presents an environment for experimentation of advanced behaviors in smart factories, allowing experimentation with multi-robot systems (MRS), interconnected, cooperative, and interacting with virtual elements. The concept of ARENA introduces a novel approach to realistic and immersive experimentation in industrial environments, aiming to evaluate new technologies aligned with the Industry 4.0. The proposed method consists of a small-scale warehouse, inspired in a real scenario characterized in this paper, managing by a group of autonomous forklifts, fully interconnected, which are embodied by a swarm of tiny robots developed and prepared to operate in the small scale scenario. The AR is employed to enhance the capabilities of swarm robots, allowing box handling and virtual forklifts. Virtual laser range finders (LRF) are specially designed as segmentation of a global RGB-D camera, to improve robot perception, allowing obstacle avoidance and environment mapping. This infrastructure enables the evaluation of new strategies to improve manufacturing productivity, without compromising the production by automation faults.
- A bio-inspired approach for robot swarm in smart factoriesPublication . Rohrich, Ronnier Frates; Teixeira, Marco Antônio Simões; Piardi, Luis; Oliveira, Andre SchneiderRecent theoretical developments have revealed that the influences and efficiency that mobile robots have brought to society in the last years are incredibly revealing and should be explored in applications for the benefit of the community and the corporate world. Access to this technology enables the development of innovative research for increasingly active industrial environments. This research constitutes a relatively new area which has emerged from the problems of the industry that aims to automate activities considered costly efficiently. A common strategy used to study mobile robots, in production, is to automate work routines through robots, but specific tasks improve specific works. This paper proposes a new approach to use a SWARM of mobile robots to solve problems in the industry based on the bio-inspired solution. The bacteria can have actions that guarantee the survival of their colony; for this purpose, a series of measures can be adopted by the bacteria constituting the colony. This approach has been widely adopted in the field of SWARM of mobile robots with technical and sensory restrictions, to realize a plausible application in the industrial environment. The results of the experiment found clear support for the methodology created, and the bio-inspired SWARM proved to be potentially useful for applications in real industrial robot solutions
- Bio-inspired distributed sensors to autonomous search of gas leak sourcePublication . Rohrich, Ronnier Frates; Piardi, Luis; Lima, José; Oliveira, Andre SchneiderThis work presents multiple small robots in an unhealthy industrial environment responsible for detecting harmful gases to humans, avoiding possible harmful effects on the body. Mixed reality is widely used, considering that the environment and gases are virtual and real small robots. Essential components for the experiments are virtual, such as gases and BioCyber-Sensors. The results establish the great potential for applications in several areas, such as industrial, biomedical, and services. The entire system was developed based on ROS (Robot Operating System), thus the ease in diversifying different applications and approaches with multiple agents. The main objective of small robots is to guaranty a healthy work environment.
- Collaborative fault detection and diagnosis architecture for industrial cyber-physical systemsPublication . Piardi, Luis; Costa, Pedro; Oliveira, Andre Schneider; Leitão, PauloIndustrial Cyber-Physical Systems (ICPS) deploy a network of connected and heterogeneous systems, integrating computational and physical components, improving production and quality. However, a fault-free system is still utopian, but methodologies related to fault detection and diagnosis are still being treated in isolation or a centralized approach, overlooking the technological advances related to ICPS such as IoT, AI and edge computing. With this in mind, the present work proposes a collaborative architecture for fault detection and diagnosis, regarding the exchange of information for collaborative detection and diagnosis adopting disruptive technologies. Laboratory-scale ICPS experiments were carried out to compare the proposed approach with the approach where each component separately intends to identify and diagnose faults. The results present a faster response generating a system more flexible and robust.
- Collaborative fuzzy controlled obstacle avoidance in a vibration-driven mobile robotPublication . Lewin, Gustavo Fontes; Fabro, João Alberto; Lima, José; Oliveira, Andre Schneider; Rohrich, Ronnier FratesSpecial care must be taken when considering robots designed to operate collaboratively, such as a swarm, to prevent these agents from being damaged due to unwanted collisions. This work proposes integrating techniques used to move robots, using the Robot Operating System (ROS) and Python’s Scikit-Fuzzy module. Thus, this work developed a fuzzy-controlled collaborative obstacle avoidance system for a type of robot whose dynamics are based on motors’ vibration. Thus, these robots were designed to participate in a swarm, and the collision must be avoided. In the search for navigation stability, optimal values were sought for the engines’ pulse width modulation (PWM).
- Collective gas sensing in a cyber-physical systemPublication . Rohrich, Ronnier Frates; Teixeira, Marco Antonio Simoes; Lima, José; Oliveira, Andre SchneiderThis paper discusses a novel collective sensing approach using autonomous sensors specially designed to monitor gas leaks and search for gas sources. The proposed collective behavior aims to improve the gas-source search by sharing information between mobile sensors and reducing the risks associated with gas leakage. The group acts as a composite sensor that can move independently to search for an optimal sensing zone. The autonomous searching behavior is bio-inspired by colonies of bacteria that continuously seek energy sources throughout their existence. Each sensor makes its own autonomous search decision, considering the group sense, to move in the direction of a better energy source. The collective approach is based on autonomous agents sharing information to achieve a collective sense of gas perception and utilizes more intelligent searching. The method is evaluated in a cyber-physical system specially developed to safely experiment with gases and mobile sensors while reproducing the realistic dynamic behavior of the gas. Experiments are performed to clarify the collective gas-sensing contributions, and the gas search is compared through multiple mobile sensors with and without collective sensing. The proposed approach is evaluated in an unhealthy environment to elucidate its effectiveness. In addition to presenting the related differences between collective and individual sensory approaches, this work contributes with analyzes of the scalability of mobile gas sensing systems. This work also contributed as a simulated semi-physical experimental system to test algorithms' performance before applying it to practice. © 2001-2012 IEEE
- Collective mapping of gas leakages to determine safe routes using multi-robot systemPublication . Rohrich, Ronnier Frates; Messias, Luís Felipe; Lima, José; Oliveira, Andre SchneiderThis article discusses a novel approach to collective mapping that uses autonomous sensors to create safe routes in environments with gas leaks. Multiple mobile sensors seek to delimit different regions and assign them different tasks according to their momentary needs. In this study, robot groups act as multiple composite sensors that can move independently according to their assigned functions. Autonomous detection, collective mapping, and collective decision-making of the robots are behaviors bioinspired by the cognitive mechanisms observed in bacterial colonies. These colonies continuously seek to maintain the lives of their species based on their collective decision-making in searching for energy sources and changing colony size. In addition, as gas dispersion in the environment increases, the received data from the sensors aids collective decision-making, assigning different functions, such as mapping, environment exploration, and route creation, to groups of mobile sensors. Depending on the momentary need, the number of sensors in each group changes. The proposed method in this study was based on real mobile robots with characteristics that enable varying levels of scalability in size. Subsequently, it was evaluated in a simulated system and developed for experimentation with gas and mobile sensors in a dynamic and realistic environment. This study further contributes to analyzing multiple tasks in homogeneous sensor groups executing different tasks. Furthermore, this work introduced a simulated experimental system to test different topologies of multiple scalable mobile sensors.
- Cooperative UAV–UGV autonomous power pylon inspection: an investigation of cooperative outdoor vehicle positioning architecturePublication . Cantieri, Álvaro R.; Ferraz, Matheus; Szekir, Guido; Teixeira, Marco António; Lima, José; Oliveira, Andre Schneider; Wehrmeister, Marco AurelioRealizing autonomous inspection, such as that of power distribution lines, through unmanned aerial vehicle (UAV) systems is a key research domain in robotics. In particular, the use of autonomous and semi-autonomous vehicles to execute the tasks of an inspection process can enhance the efficacy and safety of the operation; however, many technical problems, such as those pertaining to the precise positioning and path following of the vehicles, robust obstacle detection, and intelligent control, must be addressed. In this study, an innovative architecture involving an unmanned aircraft vehicle (UAV) and an unmanned ground vehicle (UGV) was examined for detailed inspections of power lines. In the proposed strategy, each vehicle provides its position information to the other, which ensures a safe inspection process. The results of real-world experiments indicate a satisfactory performance, thereby demonstrating the feasibility of the proposed approach.
- Deep learning-based localization approach for autonomous robots in the robotAtFactory 4.0 competitionPublication . Klein, Luan C.; Mendes, João; Braun, João; Martins, Felipe N.; Oliveira, Andre Schneider; Costa, Paulo Gomes da; Wörtche, Heinrich; Lima, JoséAccurate localization in autonomous robots enables effective decision-making within their operating environment. Various methods have been developed to address this challenge, encompassing traditional techniques, fiducial marker utilization, and machine learning approaches. This work proposes a deep-learning solution employing Convolutional Neural Networks (CNN) to tackle the localization problem, specifically in the context of the RobotAtFactory 4.0 competition. The proposed approach leverages transfer learning from the pre-trained VGG16 model to capitalize on its existing knowledge. To validate the effectiveness of the approach, a simulated scenario was employed. The experimental results demonstrated an error within the millimeter scale and rapid response times in milliseconds. Notably, the presented approach offers several advantages, including a consistent model size regardless of the number of training images utilized and the elimination of the need to know the absolute positions of the fiducial markers.
- DepthLiDAR: active segmentation of environment depth map into mobile sensorsPublication . Limeira, Marcelo A.; Piardi, Luis; Kalempa, Vivian Cremer; Leitão, Paulo; Oliveira, Andre SchneiderThis paper presents a novel approach for creating virtual LiDAR scanners through the active segmentation of point clouds. The method employs top-view point cloud segmentation in virtual LiDAR sensors that can be applied to the intelligent behavior of autonomous agents. Segmentation is correlated with the visual tracking of the agent for localization in the environmentand point cloud. Virtual LiDARsensors with different characteristicsand positions can then be generated. Thismethod is referred to as the DepthLiDAR approach, and is rigorously evaluated to quantify its performance and determine its advantages and limitations. An extensive set of experiments is conducted using real and virtual LiDAR sensors to compare both approaches. The objective is to propose a novel method to incorporate spatial perception in warehouses, aiming to achieve Industry 4.0. Thus, it is tested in a low-scale warehouse to incorporate realistic features. The analysis of the experiments shows a measurement improvement of 52.24% compared to the conventional LiDAR.
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