Search results for: autonomous drones

Authors: Mortez Alijani, Anas Osman

Abstract:

Recently, the popularity of Unmanned aerial vehicles (UAVs) has skyrocketed amidst the unprecedented events and the global pandemic, as they play a key role in both the security and health sectors, through surveillance, taking test samples, transportation of crucial goods and spreading awareness among civilians. However, the process of designing and producing such aerial robots is suppressed by the internal and external constraints that pose serious challenges. Landing is one of the key operations during flight, especially, the autonomous landing of UAVs on a moving platform is a scientifically complex engineering problem. Typically having a successful automatic landing of UAV on a moving platform requires accurate localization of landing, fast trajectory planning, and robust control planning. To achieve these goals, the information about the autonomous landing process such as the intersection point, the position of platform/UAV and inclination angle are more necessary. In this study, the mathematical approach to this problem in the X-Y axis based on the inclination angle and position of UAV in the landing process have been presented. The experimental results depict the accurate position of the UAV, intersection between UAV and moving platform and inclination angle in the landing process, allowing prediction of the intersection point.

Keywords: autonomous landing, inclination angle, unmanned aerial vehicles, moving platform, X-Y axis, intersection point

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Authors: Arwa Khannoussi, Alexandru-Liviu Olteanu, Pritesh Narayan, Catherine Dezan, Jean-Philippe Diguet, Patrick Meyer, Jacques Petit-Frere

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Due to the nature of autonomous Unmanned Aerial Vehicles (UAV) missions, it is important that the decisions of a UAV stay consistent with the priorities of an operator, while at the same time allowing them to be easily audited and explained. We propose a multi-layer decision engine that integrates the operator (human) preferences by using the Multi-Criteria Decision Aiding (MCDA) methods. A software implementation of a UAV simulator and of the decision engine is presented to highlight the advantage of using such techniques on high-level decisions. We demonstrate that, with such a preference-based decision engine, the decisions of the UAV are compatible with the priorities of the operator, which in turn increases her/his confidence in its autonomous behavior.

Keywords: autonomous UAV, multi-criteria decision aiding, multi-layers decision engine, operator's preferences, traceable decisions, UAV simulation

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Authors: Mahdi Allaoua Seklab, Süleyman BaşTürk

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In the quest to enhance coastal environmental health, this study introduces a fully autonomous beach cleaning machine, a breakthrough in leveraging green energy and advanced artificial intelligence for ecological preservation. Designed to operate independently, the machine is propelled by a solar-powered system, underscoring a commitment to sustainability and the use of renewable energy in autonomous robotics. The vehicle's autonomous navigation is achieved through a sophisticated integration of LIDAR and a camera system, utilizing an SSD MobileNet V2 object detection model for accurate and real-time trash identification. The SSD framework, renowned for its efficiency in detecting objects in various scenarios, is coupled with the lightweight and precise highly MobileNet V2 architecture, making it particularly suited for the computational constraints of on-board processing in mobile robotics. Training of the SSD MobileNet V2 model was conducted on Google Colab, harnessing cloud-based GPU resources to facilitate a rapid and cost-effective learning process. The model was refined with an extensive dataset of annotated beach debris, optimizing the parameters using the Adam optimizer and a cross-entropy loss function to achieve high-precision trash detection. This capability allows the machine to intelligently categorize and target waste, leading to more effective cleaning operations. This paper details the design and functionality of the beach cleaning machine, emphasizing its autonomous operational capabilities and the novel application of AI in environmental robotics. The results showcase the potential of such technology to fill existing gaps in beach maintenance, offering a scalable and eco-friendly solution to the growing problem of coastal pollution. The deployment of this machine represents a significant advancement in the field, setting a new standard for the integration of autonomous systems in the service of environmental stewardship.

Keywords: autonomous beach cleaning machine, renewable energy systems, coastal management, environmental robotics

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Authors: Yingxu Wang, Jianhua Lu, Jun Peng, Jiawei Zhang

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The fundamental demand in contemporary intelligent science towards Autonomous AI (AI*) is the creation of unprecedented formal means of Intelligent Mathematics (IM). It is discovered that natural intelligence is inductively created rather than exhaustively trained. Therefore, IM is a family of algebraic and denotational mathematics encompassing Inference Algebra, Real-Time Process Algebra, Concept Algebra, Semantic Algebra, Visual Frame Algebra, etc., developed in our labs. IM plays indispensable roles in training-free AI* theories and systems beyond traditional empirical data-driven technologies. A set of applications of IM-driven AI* systems will be demonstrated in contemporary intelligence science, AI*, and cognitive computers.

Keywords: intelligence mathematics, foundations of intelligent science, autonomous AI, cognitive computers, inference algebra, real-time process algebra, concept algebra, semantic algebra, applications

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Authors: Changchun Liang, Xiaodong Zhang, Xin Liu, Pengfei Sun

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Space intelligent robotic systems are expected to play an increasingly important role in the future. The robotic on-orbital service, whose key is the tracking and capturing technology, becomes research hot in recent years. In this paper, the authors propose a vision servo control system for target capturing. Robotic manipulator will be an intelligent robotic system with large-scale movement, functional agility, and autonomous ability, and it can be operated by astronauts in the space station or be controlled by the ground operator in the remote operation mode. To realize the autonomous movement and capture mission of SRM, a kind of autonomous programming strategy based on multi-camera vision fusion is designed and the selection principle of object visual position and orientation measurement information is defined for the better precision. Distributed control system hierarchy is designed and reliability is considering to guarantee the abilities of control system. At last, a ground experiment system is set up based on the concept of robotic control system. With that, the autonomous target capturing experiments are conducted. The experiment results validate the proposed algorithm, and demonstrates that the control system can fulfill the needs of function, real-time and reliability.

Keywords: control system, on-orbital service, space robot, vision servo

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Authors: Tesfaye Mengistu

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This thesis aims to investigate the effectiveness of Reinforcement Learning (RL) for Autonomous Energy Management solutions. The study explores the potential of Model Free RL approaches, such as Monte Carlo RL and Q-learning, to improve energy management by autonomously adjusting energy management strategies to maximize efficiency. The research investigates the implementation of RL algorithms for optimizing energy consumption in a single-agent environment. The focus is on developing a framework for the implementation of RL algorithms, highlighting the importance of RL for enabling autonomous systems to adapt quickly to changing conditions and make decisions based on previous experiences. Moreover, the paper proposes RL as a novel energy management solution to address nations' CO2 emission goals. Reinforcement learning algorithms are well-suited to solving problems with sequential decision-making patterns and can provide accurate and immediate outputs to ease the planning and decision-making process. This research provides insights into the challenges and opportunities of using RL for energy management solutions and recommends further studies to explore its full potential. In conclusion, this study provides valuable insights into how RL can be used to improve the efficiency of energy management systems and supports the use of RL as a promising approach for developing autonomous energy management solutions in residential buildings.

Keywords: artificial intelligence, reinforcement learning, monte carlo, energy management, CO2 emission

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Authors: Qing Dai, Zhengkui Lin, Jiajia Zhang, Yi Qu

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Based on activity method, this paper focuses on morning commuting behavior when commuters travel with autonomous vehicles (AVs). Firstly, a net utility function of commuters is constructed by the activity utility of commuters at home, in car and at workplace, and the disutility of travel time cost and that of schedule delay cost. Then, this net utility function is applied to build an equilibrium model. Finally, under the assumption of constant marginal activity utility, the properties of equilibrium are analyzed. The results show that, in autonomous driving, the starting and ending time of morning peak and the number of commuters who arrive early and late at workplace are the same as those in manual driving. In automatic driving, however, the departure rate of arriving early at workplace is higher than that of manual driving, while the departure rate of arriving late is just the opposite. In addition, compared with manual driving, the departure time of arriving at workplace on time is earlier and the number of people queuing at the bottleneck is larger in automatic driving. However, the net utility of commuters and the total net utility of system in automatic driving are greater than those in manual driving.

Keywords: autonomous cars, bottleneck model, activity utility, user equilibrium

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Authors: Pierre Kancir, Jean-Philippe Diguet, Marc Sevaux

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One of the main difficulties in developing multi-robot systems (MRS) is related to the simulation and testing tools available. Indeed, if the differences between simulations and real robots are too significant, the transition from the simulation to the robot won’t be possible without another long development phase and won’t permit to validate the simulation. Moreover, the testing of different algorithmic solutions or modifications of robots requires a strong knowledge of current tools and a significant development time. Therefore, the availability of tools for MRS, mainly with flying drones, is crucial to enable the industrial emergence of these systems. This research aims to present the most commonly used tools for MRS simulations and their main shortcomings and presents complementary tools to improve the productivity of designers in the development of multi-vehicle solutions focused on a fast learning curve and rapid transition from simulations to real usage. The proposed contributions are based on existing open source tools as Gazebo simulator combined with ROS (Robot Operating System) and the open-source multi-platform autopilot ArduPilot to bring them to a broad audience.

Keywords: ROS, ArduPilot, MRS, simulation, drones, Gazebo

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Authors: Julio Manuel de Luis Ruiz, Javier Sedano Cibrián, Rubén Pérez Álvarez, Raúl Pereda García, Cristina Diego Soroa

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Nowadays, the use of drones has been extended to practically any human activity. One of the main applications is focused on the surveying field. In this regard, software programs that process the images captured by the sensor from the drone in an almost automatic way have been developed and commercialized, but they only allow contrasting the results through control points. This work proposes the contrast of a 3D model obtained from a flight developed by a drone and a non-metric camera (due to its low cost), with a second model that is obtained by means of the historically-endorsed classical methods. In addition to this, the contrast is developed over a certain territory with a significant unevenness, so as to test the model generated with photogrammetry, and considering that photogrammetry with drones finds more difficulties in terms of accuracy in this kind of situations. Distances, heights, surfaces and volumes are measured on the basis of the 3D models generated, and the results are contrasted. The differences are about 0.2% for the measurement of distances and heights, 0.3% for surfaces and 0.6% when measuring volumes. Although they are not important, they do not meet the order of magnitude that is presented by salespeople.

Keywords: accuracy, classical topographic, model tridimensional, photogrammetry, Uav.

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Authors: R. L. P. de Lima, F. C. B. Boogaard, D. Setyo Rini, P. Arisandi, R. E. de Graaf-Van Dinther

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Water quality in many Asian countries is very poor due to inefficient solid waste management, high population growth and the lack of sewage and purification systems for households and industry. A consortium of Indonesian and Dutch organizations has begun a large-scale international research project to evaluate and propose solutions to face the surface water pollution challenges in Brantas Basin, Indonesia (East Java: Malang / Surabaya). The first phase of the project consisted in a baseline study to assess the current status of surface water bodies and to determine the ambitions and strategies among local stakeholders. This study was conducted with high participatory / collaborative and knowledge sharing objectives. Several methods such as using mobile sensors (attached to boats or underwater drones), test strips and mobile apps, bio-monitoring (sediments), ecology scans using underwater cameras, or continuous / static measurements, were applied in different locations in the regions of the basin, at multiple locations within the water systems (e.g. spring, upstream / downstream of industry and urban areas, mouth of the Surabaya River, groundwater). Results gave an indication of (reference) values of basic water quality parameters such as turbidity, electrical conductivity, dissolved oxygen or nutrients (ammonium / nitrate). An important outcome was that collecting random samples may not be representative of a body of water, given that water quality parameters can vary widely in space (x, y, and depth) and time (day / night and seasonal). Innovative / dynamic monitoring methods (e.g. underwater drones, sensors on boats) can contribute to better understand the quality of the living environment (water, ecology, sediment) and factors that affect it. The field work activities, in particular, underwater drones, revealed potential as awareness actions as they attracted interest from locals and local press. This baseline study involved the cooperation with local managing organizations with Dutch partners, and their willingness to work together is important to ensure participatory actions and social awareness regarding the process of adaptation and strengthening of regulations, or for the construction of facilities such as sewage.

Keywords: water quality monitoring, pollution, underwater drones, social awareness

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Authors: Chin-Shan Lu, Yi-Pei Liu

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This study examines the factors influencing the adoption of MASS in Taiwan's shipping industry. Digital technology and unmanned vehicle advancements have enhanced efficiency and reduced environmental impact in the shipping industry. The IMO has set regulations to promote low-carbon emissions and autonomous ship technology. Using the TOE framework and DOI theory, a research model was constructed, and data from 132 Taiwanese shipping companies were collected via a questionnaire survey. A structural equation modeling (SEM) was conducted to examine the relationships between variables. Results show that technological and environmental factors significantly influence operators' attitudes toward MASS, while organizational factors impact their willingness to adopt. Enhancing technological support, internal resource allocation, top management support, and cost management are crucial for promoting adoption. This study identifies key factors and provides recommendations for adopting autonomous ships in Taiwan's shipping industry.

Keywords: MASS, technology-organization-environment, diffusion of innovations theory, shipping industry

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Authors: Emily J. Morey, Kevin Galvin, Thomas Riley, R. Eddie Wilson

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The key challenges faced by integrating autonomous rail operations into the existing mainline railway environment have been identified through the understanding and framing of the problem space and stakeholder analysis. This was achieved through the completion of the first four steps of Soft Systems Methodology, where the problem space has been expressed via conceptual models. Having identified these challenges, we investigated one of them, namely capacity, via the use of models and simulation. This paper examines the approach used to move from the conceptual models to a simulation which can determine whether the integration of autonomous trains can plausibly increase capacity. Within this approach, we developed an architecture and converted logical models into physical resource models and associated design features which were used to build a simulator. From this simulator, we are able to analyse mixtures of legacy-autonomous operations and produce fundamental diagrams and trajectory plots to describe the dynamic behaviour of mixed mainline railway operations.

Keywords: autonomy, executable architecture, modelling and simulation, railway capacity

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Authors: Sebastian van Delden, Matthew Anuszkiewicz, Jayse White, Scott Stolarski

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Industrial robotic manipulators have been commonplace in the manufacturing world since the early 1960s, and unmanned aerial vehicles (drones) have only begun to realize their full potential in the service industry and the military. The omnipresence of these technologies in their respective fields will only become more potent in coming years. While these technologies have greatly evolved over the years, the typical approach to human interaction with these robots has not. In the industrial robotics realm, a manipulator is typically jogged around using a teach pendant and programmed using a networked computer or the teach pendant itself via a proprietary software development platform. Drones are typically controlled using a two-handed controller equipped with throttles, buttons, and sticks, an app that can be downloaded to one’s mobile device, or a combination of both. This application-oriented work offers a novel approach to human interaction with both unmanned aerial vehicles and industrial robotic manipulators via hand gestures and movements. Two systems have been implemented, both of which use a Myo™ armband to control either a drone (DJI Spark™) or a robotic arm (Stäubli™ TX40). The methodologies developed by this work present a mapping of armband gestures (fist, finger spread, swing hand in, swing hand out, swing arm left/up/down/right, etc.) to either drone or robot arm movements. The findings of this study present the efficacy and limitations (precision and ergonomic) of hand gesture control of two distinct types of robotic technology. All source code associated with this project will be open sourced and placed on GitHub. In conclusion, this study offers a framework that maps hand and arm gestures to drone and robot arm control. The system has been implemented using current ubiquitous technologies, and these software artifacts will be open sourced for future researchers or practitioners to use in their work.

Keywords: human robot interaction, drones, gestures, robotics

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Authors: Akbarnejad Neda

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A foreign language acquisition occurs when we can tell a joke and understand it. Most jokes are told in slang and common language. In the process of foreign language acquisition, an autonomous learner try to learn the standard language. But there is a colossal divergence between the usage of the different types of language in society. Here, we investigate the french slang and common language and examine the accurate perception of their usage. We illuminate the slang language in the french literature that provide considerably different types of language for an autonomous learner. We provide furthermore evidence from the french novels that demonstrate properly the different types of language and give in one sentence its social meanings. For example, the famous Queneau expression « Doukipudonktant » present the impact of slang language in society. The characters in the novel transfer the slang and the common language and their accurate usages. We present that the language of the autonomous learner depends on the language of the text that is read. Because literature is a vehicle of the culture and the expression demonstrate their real significations and usage in the culture, slang and common language have a crucial role in the culture and all of them are manifested in the oral language.

Keywords: common language, french, humor, slang language

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Authors: Mohammad Moonesun, Ehsan Asadi Asrami, Julia Bodnarchuk

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In the case of Solar Autonomous Underwater Vehicle, which uses photovoltaic panels to provide its required power, due to limitation of energy, accurate estimation of resistance and energy has major sensitivity. In this work, hydrodynamic calculations by numerical method for a solar autonomous underwater vehicle equipped by two 50 W photovoltaic panels has been studied. To evaluate the required power and energy, hull hydrodynamic resistance in several velocities should be taken into account. To do this assessment, the ANSYS FLUENT 18 applied as Computational Fluid Dynamics (CFD) tool that solves Reynolds Average Navier Stokes (RANS) equations around AUV hull, and K-ω SST is used as turbulence model. To validate of solution method and modeling approach, the model of Myring submarine that it’s experimental data was available, is simulated. There is good agreement between numerical and experimental results. Also, these results showed that the K-ω SST Turbulence model is an ideal method to simulate the AUV motion in low velocities.

Keywords: underwater vehicle, hydrodynamic resistance, numerical modelling, CFD, RANS

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Authors: Espen Oland

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This paper presents a solution to the problem of autonomous rendezvous for spacecraft equipped with one main thruster for translational control and three reaction wheels for rotational control. With fewer actuators than degrees of freedom, this constitutes an underactuated control problem, requiring a coupling between the translational and rotational dynamics to facilitate control. This paper shows how to obtain this coupling, and applies the results to autonomous rendezvous between a follower spacecraft and a leader spacecraft. Additionally, since the thrust is constrained between zero and an upper bound, no negative forces can be generated to slow down the speed of the spacecraft. A combined speed and attitude control logic is therefore created that can be divided into three main phases: 1) The orbital velocity vector is pointed towards the desired position and the thrust is used to obtain the desired speed, 2) during the coasting phase, the attitude is changed to facilitate deceleration using the main thruster, 3) the speed is decreased as the spacecraft reaches its desired position. The results are validated through simulations, showing the capabilities of the proposed approach.

Keywords: attitude control, spacecraft rendezvous, translational control, underactuated rigid body

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Authors: Mohammed Qasim, Kyoung-Dae Kim

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In this paper, we present the design of the super-ellipsoidal potential function (SEPF), that can be used for autonomous collision avoidance of an unmanned aerial vehicle (UAV) in a 3-dimensional space. In the design of SEPF, we have the full control over the shape and size of the potential function. In particular, we can adjust the length, width, height, and the amount of flattening at the tips of the potential function so that the collision avoidance motion vector generated from the potential function can be adjusted accordingly. Based on the idea of the SEPF, we also propose an approach for the local autonomy of a UAV for its collision avoidance when the UAV is teleoperated by a human operator. In our proposed approach, a teleoperated UAV can not only avoid collision autonomously with other surrounding objects but also track the operator’s control input as closely as possible. As a result, an operator can always be in control of the UAV for his/her high-level guidance and navigation task without worrying too much about the UAVs collision avoidance while it is being teleoperated. The effectiveness of the proposed approach is demonstrated through a human-in-the-loop simulation of quadrotor UAV teleoperation using virtual robot experimentation platform (v-rep) and Matlab programs.

Keywords: artificial potential function, autonomous collision avoidance, teleoperation, quadrotor

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Authors: Ronald Mraz, Gary C. Kessler, Ethan Gold, John G. Cline

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The International Ice Patrol (IIP) continually monitors iceberg activity in the North Atlantic by direct observation using ships, aircraft, and satellite imagery. Daily reports detailing navigational boundaries of icebergs have significantly reduced the risk of iceberg contact. What is currently lacking is formatting this data for automatic transmission and display of iceberg navigational boundaries in commercial navigation equipment. This paper describes the methodology and implementation of a system to format iceberg limit information for dissemination through existing radio network communications. This information will then automatically display on commercial navigation equipment. Additionally, this information is reformatted for Google Earth rendering of iceberg track line limits. Having iceberg limit information automatically available in standard navigation equipment will help support full autonomous operation of sailing vessels.

Keywords: iceberg, iceberg risk, iceberg track lines, AIS messaging, international ice patrol, North American ice service, google earth, autonomous surface vessels

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Authors: Dawei Cai

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In this paper, we present an autonomous guidance service by combining the position information from NFC and the orientation information from a 6 axis acceleration and terrestrial magnetism sensor. We developed an algorithm to calculate the device orientation based on the data from acceleration and terrestrial magnetism sensor. If visitors want to know some explanation about an exhibit in front of him, what he has to do is just lift up his mobile device. The identification program will automatically identify the status based on the information from NFC and MEMS, and start playing explanation content for him. This service may be convenient for old people or disables or children.

Keywords: NFC, ubiquitous computing, guide sysem, MEMS

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Authors: Jonqlan Lin, C. Y. Tasi, K. H. Lin

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This paper addresses the issue of the autonomous mobile robot (AMR) navigation task based on the hybrid control modes. The novel hybrid control mode, based on multi-sensors information by using the fuzzy approach, has been presented in this research. The system operates in real time, is robust, enables the robot to operate with imprecise knowledge, and takes into account the physical limitations of the environment in which the robot moves, obtaining satisfactory responses for a large number of different situations. An experiment is simulated and carried out with a pioneer mobile robot. From the experimental results, the effectiveness and usefulness of the proposed AMR obstacle avoidance and navigation scheme are confirmed. The experimental results show the feasibility, and the control system has improved the navigation accuracy. The implementation of the controller is robust, has a low execution time, and allows an easy design and tuning of the fuzzy knowledge base.

Keywords: autonomous mobile robot, obstacle avoidance, MEMS, hybrid control mode, navigation control

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Authors: René A. Sørensen, Søren Skovsen, Peter Christiansen, Henrik Karstoft

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Autonomous agricultural machines act in stochastic surroundings and therefore, must be able to perceive the surroundings in real time. This perception can be achieved using image sensors combined with advanced machine learning, in particular Deep Learning. Deep convolutional neural networks excel in labeling and perceiving color images and since the cost of high-quality RGB-cameras is low, the hardware cost of good perception depends heavily on memory and computation power. This paper investigates the possibility of designing lightweight convolutional neural networks for semantic segmentation (pixel wise classification) with reduced hardware requirements, to allow for embedded usage in autonomous agricultural machines. Using compression techniques, a lightweight convolutional neural network is designed to perform real-time semantic segmentation on an embedded platform. The network is trained on two large datasets, ImageNet and Pascal Context, to recognize up to 400 individual classes. The 400 classes are remapped into agricultural superclasses (e.g. human, animal, sky, road, field, shelterbelt and obstacle) and the ability to provide accurate real-time perception of agricultural surroundings is studied. The network is applied to the case of autonomous grass mowing using the NVIDIA Tegra X1 embedded platform. Feeding case-specific images to the network results in a fully segmented map of the superclasses in the image. As the network is still being designed and optimized, only a qualitative analysis of the method is complete at the abstract submission deadline. Proceeding this deadline, the finalized design is quantitatively evaluated on 20 annotated grass mowing images. Lightweight convolutional neural networks for semantic segmentation can be implemented on an embedded platform and show competitive performance with regards to accuracy and speed. It is feasible to provide cost-efficient perceptive capabilities related to semantic segmentation for autonomous agricultural machines.

Keywords: autonomous agricultural machines, deep learning, safety, visual perception

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Authors: Hang Ju, Changmin Zhu

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The development level of the BeiDou Navigation Satellite System (BDS) can strongly reflect national defense strength as an important spatial information infrastructure. BDS can be not only used for military purposes, such as intelligence gathering, nuclear explosion monitoring, emergency communications, but also for location services, transportation, mapping, precision agriculture. In order to ensure the national defense security and the wide application of BDS in civil and military areas, BDS must be autonomous and controllable. As a complex system of knowledge-intensive, knowledge transformation runs through the whole process of research and development, production, operation, and maintenance of BDS. Based on the perspective of knowledge transformation, this paper expounds on the meaning of socialization, externalization, combination, and internalization of knowledge transformation, and the coupling relationship of autonomy and control on the basis of analyzing the status quo and problems of the autonomy and control of BDS. The autonomous and controllable framework of BDS based on knowledge transformation is constructed from six dimensions of management capability, R&D capability, technical capability, manufacturing capability, service support capability, and application capability. It can provide support for the smooth implementation of information security policy, provide a reference for the autonomy and control of the upstream and downstream industrial chains in Beidou, and provide a reference for the autonomous and controllable research of aerospace components, military measurement test equipment, and other related industries.

Keywords: knowledge transformation, BeiDou Navigation Satellite System, autonomy and control, framework

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Authors: Indraj Singh, Xuan Lee, Yu-Chieh Cheng

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Scientists are very keen on biomimetic research that mimics biological species to micro-robotic devices with the novel functionalities and accessibility. The source of inspiration is the complexity, sophistication, and intelligence of the biological systems. In this work, we design a light-driven star-shaped microgripper, an autonomous soft device which can change the shape under the external stimulus such as light. The design is based on light-responsive Liquid Crystal Elastomers which fabricated onto the polymer coated aligned substrate. The change in shape, controlled by the anisotropicity and the molecular orientation of the Liquid Crystal Elastomer, based on the external stimulus. This artificial star-shaped microgripper is capable of autonomous closure and capable to grab the objects in response to an external stimulus. This external stimulus-responsive materials design, based on soft active smart materials, provides a new approach to autonomous, self-regulating optical systems.

Keywords: liquid crystal elastomers, microgripper, smart materials, robotics

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Authors: Denis Spirjakin, Alexander Baranov, Saba Akbari, Natalia Kalenova, Vladimir Sleptsov

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In this paper we propose the approach to power management in wireless combustible gas sensors. This approach makes possible drastically prolong sensor nodes autonomous lifetime. That is necessary to tie battery replacement to every year technical service procedures which are claimed by safety standards. Using this approach the current consumption of the wireless combustible gas sensor node was decreased from 80 mA to less than 2 mA and the power consumption from more than 220 mW to 4.6 mW. These values provide autonomous lifetime of the node more than one year.

Keywords: Gas sensors, power management, wireless sensor network

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Authors: Long Cheng, Tong He, Iraj Mantegh, Wen-Fang Xie

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Path planning is essential for UAVs (Unmanned Aerial Vehicle) with autonomous navigation in unknown environments. In this paper, an adaptive probabilistic sampling algorithm is proposed for the GPS-denied environment, which can be utilized for autonomous navigation system of multiple UAVs in a dynamically-changing structured environment. This method can be used for Unmanned Aircraft Systems Traffic Management (UTM) solutions and in autonomous urban aerial mobility, where a number of platforms are expected to share the airspace. A path network is initially built off line based on available environment map, and on-board sensors systems on the flying UAVs are used for continuous situational awareness and to inform the changes in the path network. Simulation results based on MATLAB and Gazebo in different scenarios and algorithms performance measurement show the high efficiency and accuracy of the proposed technique in unknown environments.

Keywords: path planning, adaptive probabilistic sampling, obstacle avoidance, multiple unmanned aerial vehicles, unknown environments

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Authors: Seyed Jamal Haddadi, M. Reza Mehranpour, Roya Sadat Mortazavi, Zahra Sadat Mortazavi

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Principal aim of this research is trajectory tracking, attitude and position control scheme in real flight mode by an Octorotor helicopter. For more stability, in this Unmanned Aerial Vehicle (UAV), number of motors is increased to eight motors which end of each arm installed two coaxial counter rotating motors. Dynamic model of this Octorotor includes of motion equation for translation and rotation. Utilized controller is proportional-integral-derivative (PID) control loop. The proposed controller is designed such that to be able to attenuate an effect of external wind disturbance and guarantee stability in this condition. The trajectory is determined by a Global Positioning System (GPS). Also an ARM CortexM4 is used as microprocessor. Electronic board of this UAV designed as able to records all of the sensors data, similar to an aircraft black box in external memory. Finally after auto landing of Octorotor, flight data is shown in MATLAB software and Experimental results of the proposed controller show the effectiveness of our approach on the Autonomous Quadrotor in real conditions.

Keywords: octorotor, design, PID controller, autonomous, trajectory tracking

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Authors: Richard Molyneux, Christopher Parrott, Kirill Horoshenkov

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This paper aims to demonstrate how various algorithms can be implemented within swarms of autonomous robots to provide continuous inspection within underground pipeline networks. Current methods of fault detection within pipes are costly, time consuming and inefficient. As such, solutions tend toward a more reactive approach, repairing faults, as opposed to proactively seeking leaks and blockages. The paper presents an efficient inspection method, showing that autonomous swarm robotics is a viable way of monitoring underground infrastructure. Tailored adaptations of various Vehicle Routing Problems (VRP) and path-planning algorithms provide a customised inspection procedure for complicated networks of underground pipes. The performance of multiple algorithms is compared to determine their effectiveness and feasibility. Notable inspirations come from ant colonies and stigmergy, graph theory, the k-Chinese Postman Problem ( -CPP) and traffic theory. Unlike most swarm behaviours which rely on fast communication between agents, underground pipe networks are a highly challenging communication environment with extremely limited communication ranges. This is due to the extreme variability in the pipe conditions and relatively high attenuation of acoustic and radio waves with which robots would usually communicate. This paper illustrates how to optimise the inspection process and how to increase the frequency with which the robots pass each other, without compromising the routes they are able to take to cover the whole network.

Keywords: autonomous inspection, buried pipes, stigmergy, swarm intelligence, vehicle routing problem

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Authors: Mohanad Al-Behadili, Xiang Song, Djamila Ouelhadj, Alex Fraess-Ehrfeld

Abstract:

In off-shore wind farms, turbine blade inspection accessibility under various sea states is very challenging and greatly affects the downtime of wind turbines. Maintenance of any offshore system is not an easy task due to the restricted logistics and accessibility. The multirotor unmanned helicopter is of increasing interest in inspection applications due to its manoeuvrability and payload capacity. These advantages increase when many of them are deployed simultaneously in a swarm. Hence this paper proposes a drone swarm framework for inspecting offshore wind turbine blades and nacelles so as to reduce downtime. One of the big challenges of this task is that when operating a drone swarm, an individual drone may not have enough power to fly and communicate during missions and it has no capability of refueling due to its small size. Once the drone power is drained, there are no signals transmitted and the links become intermittent. Vessels equipped with 5G masts and small power units are utilised as platforms for drones to recharge/swap batteries. The research work aims at designing a smart energy management system, which provides automated vessel and drone routing and recharging plans. To achieve this goal, a novel mathematical optimisation model is developed with the main objective of minimising the number of drones and vessels, which carry the charging stations, and the downtime of the wind turbines. There are a number of constraints to be considered, such as each wind turbine must be inspected once and only once by one drone; each drone can inspect at most one wind turbine after recharging, then fly back to the charging station; collision should be avoided during the drone flying; all wind turbines in the wind farm should be inspected within the given time window. We have developed a real-time Ant Colony Optimisation (ACO) algorithm to generate real-time and near-optimal solutions to the drone swarm routing problem. The schedule will generate efficient and real-time solutions to indicate the inspection tasks, time windows, and the optimal routes of the drones to access the turbines. Experiments are conducted to evaluate the quality of the solutions generated by ACO.

Keywords: drone swarm, routing, scheduling, optimisation model, ant colony optimisation

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Authors: Sarah Pfoser, Lisa-Maria Putz, Thomas Berger

Abstract:

In the EU, the transport sector accounts for roughly one fourth of the total greenhouse gas emissions. In fact, the transport sector is one of the main contributors of greenhouse gas emissions. Climate protection targets aim to reduce the negative effects of greenhouse gas emissions (e.g. climate change, global warming) worldwide. Achieving a modal shift to foster environmentally friendly modes of transport such as rail and inland waterways is an important strategy to fulfill the climate protection targets. The present paper goes beyond these conventional transport modes and reflects upon currently emerging high-performance transport modes that yield the potential of complementing future transport systems in an efficient way. It will be defined which properties describe high-performance transport modes, which types of technology are included and what is their potential to contribute to a sustainable future transport network. The first step of this paper is to compile state-of-the-art information about high-performance transport modes to find out which technologies are currently emerging. A multidimensional impact analysis will be conducted afterwards to evaluate which of the technologies is most promising. This analysis will be performed from a spatial, social, economic and environmental perspective. Frequently used instruments such as cost-benefit analysis and SWOT analysis will be applied for the multidimensional assessment. The estimations for the analysis will be derived based on desktop research and discussions in an interdisciplinary team of researchers. For the purpose of this work, high-performance transport modes are characterized as transport modes with very fast and very high throughput connections that could act as efficient extension to the existing transport network. The recently proposed hyperloop system represents a potential high-performance transport mode which might be an innovative supplement for the current transport networks. The idea of hyperloops is that persons and freight are shipped in a tube at more than airline speed. Another innovative technology consists in drones for freight transport. Amazon already tests drones for their parcel shipments, they aim for delivery times of 30 minutes. Drones can, therefore, be considered as high-performance transport modes as well. The Trans-European Transport Networks program (TEN-T) addresses the expansion of transport grids in Europe and also includes high speed rail connections to better connect important European cities. These services should increase competitiveness of rail and are intended to replace aviation, which is known to be a polluting transport mode. In this sense, the integration of high-performance transport modes as described above facilitates the objectives of the TEN-T program. The results of the multidimensional impact analysis will reveal potential future effects of the integration of high-performance modes into transport networks. Building on that, a recommendation on the following (research) steps can be given which are necessary to ensure the most efficient implementation and integration processes.

Keywords: drones, future transport networks, high performance transport modes, hyperloops, impact analysis

Procedia PDF Downloads 332

Authors: Youngsun Moon, Yeong-Ju Go, Jong-Soo Choi

Abstract:

Most drones that currently have surveillance/reconnaissance missions are basically equipped with optical equipment, but we also need to use a microphone array to estimate the location of the acoustic source. This can provide additional information in the absence of optical equipment. The purpose of this study is to estimate Direction of Arrival (DOA) based on Time Difference of Arrival (TDOA) estimation of the acoustic source in the drone. The problem is that it is impossible to measure the clear target acoustic source because of the drone noise. To overcome this problem is to separate the drone noise and the target acoustic source using Blind Source Separation(BSS) based on Independent Component Analysis(ICA). ICA can be performed assuming that the drone noise and target acoustic source are independent and each signal has non-gaussianity. For maximized non-gaussianity each signal, we use Negentropy and Kurtosis based on probability theory. As a result, we can improve TDOA estimation and DOA estimation of the target source in the noisy environment. We simulated the performance of the DOA algorithm applying BSS algorithm, and demonstrated the simulation through experiment at the anechoic wind tunnel.

Keywords: aeroacoustics, acoustic source detection, time difference of arrival, direction of arrival, blind source separation, independent component analysis, drone

Procedia PDF Downloads 161