20 research outputs found

    Design and Fabrication of Automatic Floor Cleaner

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    Automatic floor cleaner is a system that enables cleaning of the floor by the help of highly stabilized and rapidly functionalized electronic and mechanical control system. Current project work targets to use automatic floor cleaner for large floor in house-hold purposes and office floors. The cleaning purpose is specifically carried out by continuous relative motion between a scrubber and the floor surface. During the cleaning and moving operation of vehicle a propulsion mechanism such as driven wheels and guide wheels for the dry tracking on the floor surface to be cleaned, suction of water is carried out by vacuum pump, scrubbing action is done by the scrubber directing water towards rear end. Preferably, a sweeper mechanism is mounted on the body forwarded by propulsion mechanism and operated with such control system for advance sweeping of a debris-laden floor surface. A PID controller is used to govern the motion of system which takes the input from sensor circuit and feeds it back to microcontroller which gives rise to the simulation of wheel in a synchronized manner. The new automatic floor cleaner will save huge cost of labor in future. The basic advantage of this product is that it will be cost effective and no human control is needed. Once put in on mode it will clean the whole room without any omission of surfac

    PARLOMA – A Novel Human-Robot Interaction System for Deaf-blind Remote Communication

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    Deaf-blindness forces people to live in isolation. Up to now there is no existing technological solution enabling two (or many) Deaf-blind persons to communicate remotely among them in tactile Sign Language (t-SL). When resorting to t-SL, Deaf-blind persons can communicate only with persons physically present in the same place, because they are required to reciprocally explore their hands to exchange messages. We present a preliminary version of PARLOMA, a novel system to enable remote communication between Deaf-blind persons. It is composed of a low-cost depth sensor as the only input device, paired with a robotic hand as output device. Essentially, any user can perform handshapes in front of the depth sensor. The system is able to recognize a set of handshapes that are sent over the web and reproduced by an anthropomorphic robotic hand. PARLOMA can work as a “telephone” for Deaf-blind people. Hence, it will dramatically improve life quality of Deaf-blind persons. PARLOMA has been designed in strict collaboration with the main Italian Deaf-blind associations, in order to include end-users in the design phase

    Critical Point Identification In 3D Velocity Fields

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    Classification of flow fields involving strong vortices such as those from bluff body wakes and animal locomotion can provide important insight to their hydrodynamic behavior. Previous work has successfully classified 2D flow fields based on critical points of the velocity field and the structure of an associated weighted graph using the critical points as vertices. The present work focuses on extension of this approach to 3D flows. To this end, we have used the Gauss-Bonnet theorem to find critical points and their indices in the 3D velocity vector field, which functions similarly to the Poincare-Bendixon theorem in 2D flow fields. The approach utilizes an initial search for critical points based on local flow field direction, and the Gauss-Bonnet theorem is used to refine the location of critical points by dividing the volume integral form of the Gauss-Bonnet theorem into smaller regions. The developed method is cable of locating critical points at sub-grid level precision, which is a key factor for locating critical points and determining their associated eigenvalues on coarse grids. To verify this approach, we have applied this method on sample flow fields generated from potential flow theory and numerical methods

    Connected Attribute Filtering Based on Contour Smoothness

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    Connected Attribute Filtering Based on Contour Smoothness

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    A new attribute measuring the contour smoothness of 2-D objects is presented in the context of morphological attribute filtering. The attribute is based on the ratio of the circularity and non-compactness, and has a maximum of 1 for a perfect circle. It decreases as the object boundary becomes irregular. Computation on hierarchical image representation structures relies on five auxiliary data members and is rapid. Contour smoothness is a suitable descriptor for detecting and discriminating man-made structures from other image features. An example is demonstrated on a very-high-resolution satellite image using connected pattern spectra and the switchboard platform

    Coevolutionary algorithms for the optimization of strategies for red teaming applications

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    Red teaming (RT) is a process that assists an organization in finding vulnerabilities in a system whereby the organization itself takes on the role of an “attacker” to test the system. It is used in various domains including military operations. Traditionally, it is a manual process with some obvious weaknesses: it is expensive, time-consuming, and limited from the perspective of humans “thinking inside the box”. Automated RT is an approach that has the potential to overcome these weaknesses. In this approach both the red team (enemy forces) and blue team (friendly forces) are modelled as intelligent agents in a multi-agent system and the idea is to run many computer simulations, pitting the plan of the red team against the plan of blue team. This research project investigated techniques that can support automated red teaming by conducting a systematic study involving a genetic algorithm (GA), a basic coevolutionary algorithm and three variants of the coevolutionary algorithm. An initial pilot study involving the GA showed some limitations, as GAs only support the optimization of a single population at a time against a fixed strategy. However, in red teaming it is not sufficient to consider just one, or even a few, opponent‟s strategies as, in reality, each team needs to adjust their strategy to account for different strategies that competing teams may utilize at different points. Coevolutionary algorithms (CEAs) were identified as suitable algorithms which were capable of optimizing two teams simultaneously for red teaming. The subsequent investigation of CEAs examined their performance in addressing the characteristics of red teaming problems, such as intransitivity relationships and multimodality, before employing them to optimize two red teaming scenarios. A number of measures were used to evaluate the performance of CEAs and in terms of multimodality, this study introduced a novel n-peak problem and a new performance measure based on the Circular Earth Movers‟ Distance. Results from the investigations involving an intransitive number problem, multimodal problem and two red teaming scenarios showed that in terms of the performance measures used, there is not a single algorithm that consistently outperforms the others across the four test problems. Applications of CEAs on the red teaming scenarios showed that all four variants produced interesting evolved strategies at the end of the optimization process, as well as providing evidence of the potential of CEAs in their future application in red teaming. The developed techniques can potentially be used for red teaming in military operations or analysis for protection of critical infrastructure. The benefits include the modelling of more realistic interactions between the teams, the ability to anticipate and to counteract potentially new types of attacks as well as providing a cost effective solution

    Tracking and Hands Motion Detection Approach for Monitoring Hand-Hygiene Compliance for Food Handling and Processing Industry

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    Hand-hygiene is a very critical issue for both food handling and processing industry and health care service providers. Poor hand-hygiene practice can easily lead to foodborne illness or large scale decease transmission. In this research, an automatic tracking and monitoring system was developed that used a 3D camera for hand washing and hands motion detection and a sensor-based monitoring system for hand-hygiene activities evaluation. An active Wi-Fi portable Radio Frequency Identification (RFID) tag was used for personal ID tracking. The effective hand washing time, soaping time were measured based on the hands motion detection and hand movement tracking. Water temperature, water flow, paper towel, soap and hand sanitizer usage were also measured for each hand washing event. All the data were forwarded to a system server for data recording, storage and management. Preliminary test data were collected to evaluate the system performance. The results showed that the system could effectively collect most of the hand-hygiene related factors including hand-hygiene product usage, hand washing time and soap lathering time for hand-hygiene evaluation.Biosystems & Agricultural Engineerin

    Adaptive control system of slotless DC linear motor

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    Slotless DC linear motors (SDCLM) offer several benefits over traditional linear motors, including higher efficiency, smoother operation, and higher power density. These advantages make them a popular choice for a wide range of applications in various industries. One of the main benefits of a slotless DC linear motor is the absence of slot harmonics, which can cause vibration and noise in traditional slotted motors. This makes slotless motors ideal for applications that require precise and smooth motion, such as in medical equipment, robotics, and semiconductor manufacturing. However, one of the challenges of a Slotless DC linear motor is the presence of force ripple, which can limit the motor's performance, precision, and accuracy. Force ripple is caused by the mutual attraction of the translator's magnets and iron cores. It is independent of the motor current and is determined only by the relative position of the motor coils regarding the magnets. To overcome these challenges, motor redesign, magnetic field optimisation and the use of an adaptive control system. This research program focused on and investigated the above possible methods (i.e., motor redesign, magnetic field optimisation field and use of advanced control algorithms such as Sliding Mode Control SMC) to tackle the current challenges and improve the relevant industrial application performance and precision. The inquiry encompasses the analysis, design, and control of the SDCLM by proper modelling, building, and experimental validation of the modelled findings, applying both static and dynamic methodologies. Electrical, mechanical, and magnetic analyses were performed on the SDCLM design. The performance of the SDCLM was investigated using a finite element method (FEM), and the motor parameters were improved. Investigation and analysis are performed about additional difficulties such as force ripple and normal force, where the results indicated that the flux density in the airgap and the thrust force were different between the actual time and the simulation by 7.14% and 8.07%, respectively. Moreover, sliding mode control is designed to achieve desired system performance, such as reducing the power ripple of a slotless DC linear motor. where the proposed control shows experiments that it has stability despite disturbances and uncertainties. To improve the control method and reduce the steady-state error caused by the force ripple, the Bees algorithm has been used to tune the parameters of the controller. Finally, the outcomes indicate that the control method employing the disturbance observer and Bees algorithm has enhanced the performance of both position and speed, while concurrently reducing the force ripple. A comparison between simulation and experiment shows that there is a difference in the tracking performance, where the difference was around 13.6%. This error could have arisen from the omission of certain errors that cannot be accounted for within the simulation. These errors may stem from issues with the position sensor or discrepancies in the manual system design process

    Mobile Robots Navigation

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    Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described
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