Search results for: autonomous landing

Authors: Masoud Mirzaee, Ghobad Behzadi Pour

Abstract:

An aircraft tire is designed to tolerate extremely heavy loads for a short duration. The number of tires increases with the weight of the aircraft, as it is needed to be distributed more evenly. Generally, aircraft tires work at high pressure, up to 200 psi (14 bar; 1,400 kPa) for airliners and higher for business jets. Tire assemblies for most aircraft categories provide a recommendation of compressed nitrogen that supports the aircraft’s weight on the ground, including a mechanism for controlling the aircraft during taxi, takeoff; landing; and traction for braking. Accurate tire pressure is a key factor that enables tire assemblies to perform reliably under high static and dynamic loads. Concerning ambient temperature change, considering the condition in which the temperature between the origin and destination airport was different, tire pressure should be adjusted and inflated to the specified operating pressure at the colder airport. This adjustment superseding the normal tire over an inflation limit of 5 percent at constant ambient temperature is required because the inflation pressure remains constant to support the load of a specified aircraft configuration. On the other hand, without this adjustment, a tire assembly would be significantly under/over-inflated at the destination. Due to an increase of human errors in the aviation industry, exorbitant costs are imposed on the airlines for providing consumable parts such as aircraft tires. The existence of an intelligent system to adjust the aircraft tire pressure based on weight, load, temperature, and weather conditions of origin and destination airports, could have a significant effect on reducing the aircraft maintenance costs, aircraft fuel and further improving the environmental issues related to the air pollution. An intelligent tire pressure regulation system (ITPRS) contains a processing computer, a nitrogen bottle with 1800 psi, and distribution lines. Nitrogen bottle’s inlet and outlet valves are installed in the main wheel landing gear’s area and are connected through nitrogen lines to main wheels and nose wheels assy. Controlling and monitoring of nitrogen will be performed by a computer, which is adjusted according to the calculations of received parameters, including the temperature of origin and destination airport, the weight of cargo loads and passengers, fuel quantity, and wind direction. Correct tire inflation and deflation are essential in assuring that tires can withstand the centrifugal forces and heat of normal operations, with an adequate margin of safety for unusual operating conditions such as rejected takeoff and hard landings. ITPRS will increase the performance of the aircraft in all phases of takeoff, landing, and taxi. Moreover, this system will reduce human errors, consumption materials, and stresses imposed on the aircraft body.

Keywords: avionic system, improve efficiency, ITPRS, human error, reduced cost, tire pressure

Procedia PDF Downloads 208

Authors: Venkataramana Sovenahalli Badigar, B. M. Suryakanth, Akshar Prasanna, Karthik Veeramalai, Vishwak Ram Vishwak Ram

Abstract:

Technological advances have led to widespread autonomy in vehicles. Empowering these autonomous with the intelligence to cooperate amongst themselves leads to a more efficient use of the resources available to them. This paper proposes a demonstration of a swarm algorithm implemented on a group of autonomous vehicles. The demonstration involves two ground bots and an aerial drone which cooperate amongst them to locate an object of interest. The object of interest is modelled using a high-intensity light source which acts as a beacon. The ground bots are light sensitive and move towards the beacon. The ground bots and the drone traverse in random paths and jointly locate the beacon. This finds application in various scenarios in where human interference is difficult such as search and rescue during natural disasters, delivering crucial packages in perilous situations, etc. Experimental results show that the modified swarm algorithm implemented in this system has better performance compared to fully random based moving algorithm for object localization and tracking.

Keywords: swarm algorithm, object localization, ground bots, drone, beacon

Procedia PDF Downloads 225

Authors: David L. Olson, Stephen B. H. Bruder, Adam S. Watkins, Cleon E. Davis

Abstract:

In global navigation satellite systems (GNSS), denied settings such as indoor environments, autonomous mobile robots are often limited to dead-reckoning navigation techniques to determine their position, velocity, and attitude (PVA). Localization is typically accomplished by employing an inertial measurement unit (IMU), which, while precise in nature, accumulates errors rapidly and severely degrades the localization solution. Standard sensor fusion methods, such as Kalman filtering, aim to fuse precise IMU measurements with accurate aiding sensors to establish a precise and accurate solution. In indoor environments, where GNSS and no other a priori information is known about the environment, effective sensor fusion is difficult to achieve, as accurate aiding sensor choices are sparse. However, an opportunity arises by employing a depth camera in the indoor environment. A depth camera can capture point clouds of the surrounding floors and walls. Extracting attitude from these surfaces can serve as an accurate aiding source, which directly combats errors that arise due to gyroscope imperfections. This configuration for sensor fusion leads to a dramatic reduction of PVA error compared to traditional aiding sensor configurations. This paper provides the theoretical basis for the depth camera aiding sensor method, initial expectations of performance benefit via simulation, and hardware implementation, thus verifying its veracity. Hardware implementation is performed on the Quanser Qbot 2™ mobile robot, with a Vector-Nav VN-200™ IMU and Kinect™ camera from Microsoft.

Keywords: autonomous mobile robotics, dead reckoning, depth camera, inertial navigation, Kalman filtering, localization, sensor fusion

Procedia PDF Downloads 180

Authors: Ruby Jean Hornsby

Abstract:

In our rapidly advancing techno-moral world, human-robot relationships are increasingly becoming a part of intimate human life. Indeed, social robots - that is, autonomous or semi-autonomous embodied artificial agents that generally possess human or animal-like qualities (such as responding to environmental stimuli, communicating, learning, performing human tasks, and making autonomous decisions) - have been designed to function as human friends. In light of such advances, immediate philosophical scrutiny is imperative in order to examine the extent to which human-robot interactions constitute genuine friendship and therefore contribute towards the good human life. Aristotle's conception of friendship is philosophically illuminating and sufficiently broad in scope to guide such analysis. On his account, it is necessary (though not sufficient) that for a friendship to exist between two agents - A and B - both agents must have a mutual love for one another. Aristotle claims that A loves B if: Condition 1: A desires those apparent good (qua pleasant, useful, or virtuous) properties attributable to B, and Condition 2: A has goodwill (wishes what is best) for B. This paper argues that human-robot interaction can (and does) successfully meet both conditions; as such, it demonstrates that robots and humans can reciprocally love one another. It will argue for this position by first justifying the claim that a human can desire apparent good features attributable to a robot (i.e., by taking them to be pleasant and/or useful) and outlining how it is that a human can wish a robot well in light of that robot's (quasi-) interests. Next, the paper will argue that a robot can (quasi-)desire certain properties that are attributable to a human before elucidating how it is possible for a robot to act in the interests of a human. Accordingly, this paper will conclude that it is already the case that humans can formulate relationships with robots that involve reciprocated love. This is significant because it suggests that social robots are candidates for human friendship and can therefore contribute toward flourishing human futures.

Keywords: ancient philosophy, friendship, inter-disciplinary applied ethics, love, social robotics

Procedia PDF Downloads 81

Authors: Divya Agarwal, Pushpendra S. Bharti

Abstract:

Autonomous mobile robots (AMR) are expected as smart tools for operations in every automation industry. Path planning and obstacle avoidance is the backbone of AMR as robots have to reach their goal location avoiding obstacles while traversing through optimized path defined according to some criteria such as distance, time or energy. Path planning can be classified into global and local path planning where environmental information is known and unknown/partially known, respectively. A number of sensors are used for data collection. A number of algorithms such as artificial potential field (APF), rapidly exploring random trees (RRT), bidirectional RRT, Fuzzy approach, Purepursuit, A* algorithm, vector field histogram (VFH) and modified local path planning algorithm, etc. have been used in the last three decades for path planning and obstacle avoidance for AMR. This paper makes an attempt to review some of the path planning and obstacle avoidance algorithms used in the field of AMR. The review includes comparative analysis of simulation and mathematical computations of path planning and obstacle avoidance algorithms using MATLAB 2018a. From the review, it could be concluded that different algorithms may complete the same task (i.e. with a different set of instructions) in less or more time, space, effort, etc.

Keywords: path planning, obstacle avoidance, autonomous mobile robots, algorithms

Procedia PDF Downloads 200

Authors: Yangzhi Li

Abstract:

Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

Procedia PDF Downloads 54

Authors: Loha Hashimy, Isabella Castillo

Abstract:

In today's rapidly evolving technological landscape, the importance of precise navigation and mapping systems cannot be understated. As various sectors undergo transformative changes, the market potential for Advanced Mapping and Management Systems (AMMS) emerges as a critical focus area. The Galileo/GNSS-Based Autonomous Mobile Mapping System (GAMMS) project, specifically targeted toward high-definition mapping (HDM), endeavours to provide insights into this market within the broader context of the geomatics and navigation fields. With the growing integration of Autonomous Vehicles (AVs) into our transportation systems, the relevance and demand for sophisticated mapping solutions like HDM have become increasingly pertinent. The research employed a meticulous, lean, stepwise, and interconnected methodology to ensure a comprehensive assessment. Beginning with the identification of pivotal project results, the study progressed into a systematic market screening. This was complemented by an exhaustive desk research phase that delved into existing literature, data, and trends. To ensure the holistic validity of the findings, extensive consultations were conducted. Academia and industry experts provided invaluable insights through interviews, questionnaires, and surveys. This multi-faceted approach facilitated a layered analysis, juxtaposing secondary data with primary inputs, ensuring that the conclusions were both accurate and actionable. Our investigation unearthed a plethora of drivers steering the HD maps landscape. These ranged from technological leaps, nuanced market demands, and influential economic factors to overarching socio-political shifts. The meteoric rise of Autonomous Vehicles (AVs) and the shift towards app-based transportation solutions, such as Uber, stood out as significant market pull factors. A nuanced PESTEL analysis further enriched our understanding, shedding light on political, economic, social, technological, environmental, and legal facets influencing the HD maps market trajectory. Simultaneously, potential roadblocks were identified. Notable among these were barriers related to high initial costs, concerns around data quality, and the challenges posed by a fragmented and evolving regulatory landscape. The GAMMS project serves as a beacon, illuminating the vast opportunities that lie ahead for the HD mapping sector. It underscores the indispensable role of HDM in enhancing navigation, ensuring safety, and providing pinpoint, accurate location services. As our world becomes more interconnected and reliant on technology, HD maps emerge as a linchpin, bridging gaps and enabling seamless experiences. The research findings accentuate the imperative for stakeholders across industries to recognize and harness the potential of HD mapping, especially as we stand on the cusp of a transportation revolution heralded by Autonomous Vehicles and advanced geomatic solutions.

Keywords: high-definition mapping (HDM), autonomous vehicles, PESTEL analysis, market drivers

Procedia PDF Downloads 49

Authors: Mohammad Y. Abualhoul, Edgar Talavera Munoz, Fawzi Nashashibi

Abstract:

The new emerging Visible Light Communication (VLC) technology has been subjected to intensive investigation, evaluation, and lately, deployed in the context of convoy-based applications for Intelligent Transportations Systems (ITS). The technology limitations were defined and supported by different solutions proposals to enhance the crucial alignment and mobility limitations. In this paper, we propose the incorporation of VLC technology and Lane-Centering (LC) technique to assure the VLC-connectivity by keeping the autonomous vehicle aligned to the lane center using vision-based lane detection in a convoy-based formation. Such combination can ensure the optical communication connectivity with a lateral error less than 30 cm. As soon as the road lanes are detectable, the evaluated system showed stable behavior independently from the inter-vehicle distances and without the need for any exchanged information of the remote vehicles. The evaluation of the proposed system is verified using VLC prototype and an empirical result of LC running application over 60 km in Madrid M40 highway.

Keywords: visible light communication, lane-centerin, platooning, intelligent transportation systems, road safety applications

Procedia PDF Downloads 142

Authors: Michael Naderhirn, Marco Pavone

Abstract:

Problem statement, motivation, and aim of work: So far, the development of control algorithms was done by control engineers in a way that the controller would fit a specification by testing. When it comes to the certification of an autonomous car in highly complex scenarios, the challenge is much higher since such a controller must mathematically guarantee to implement the rules of the road while on the other side guarantee aspects like safety and real time executability. What if it becomes reality to solve this demanding problem by combining Formal Verification and System Theory? The aim of this work is to present a workflow to solve the above mentioned problem. Summary of the presented results / main outcomes: We show the usage of an English like language to transform the rules of the road into system specification for an autonomous car. The language based specifications are used to define system functions and interfaces. Based on that a formal model is developed which formally correctly models the specifications. On the other side, a mathematical model describing the systems dynamics is used to calculate the systems reachability set which is further used to determine the system input boundaries. Then a motion planning algorithm is applied inside the system boundaries to find an optimized trajectory in combination with the formal specification model while satisfying the specifications. The result is a control strategy which can be applied in real time independent of the scenario with a mathematical guarantee to satisfy a predefined specification. We demonstrate the applicability of the method in simulation driving scenarios and a potential certification. Originality, significance, and benefit: To the authors’ best knowledge, it is the first time that it is possible to show an automated workflow which combines a specification in an English like language and a mathematical model in a mathematical formal verified way to synthesizes a controller for potential real time applications like autonomous driving.

Keywords: formal system verification, reachability, real time controller, hybrid system

Procedia PDF Downloads 216

Authors: Richard O’Riordan, Saritha Unnikrishnan

Abstract:

Autonomous Vehicles (AVs) are incorporating an increasing number of ADAS features, including automated lane-keeping systems. In recent years, many research papers into lane detection algorithms have been published, varying from computer vision techniques to deep learning methods. The transition from lower levels of autonomy defined in the SAE framework and the progression to higher autonomy levels requires increasingly complex models and algorithms that must be highly reliable in their operation and functionality capacities. Furthermore, these algorithms have no room for error when operating at high levels of autonomy. Although the current research details existing computer vision and deep learning algorithms and their methodologies and individual results, the research also details challenges faced by the algorithms and the resources needed to operate, along with shortcomings experienced during their detection of lanes in certain weather and lighting conditions. This paper will explore these shortcomings and attempt to implement a lane detection algorithm that could be used to achieve improvements in AV lane detection systems. This paper uses a pre-trained LaneNet model to detect lane or non-lane pixels using binary segmentation as the base detection method using an existing dataset BDD100k followed by a custom dataset generated locally. The selected roads will be modern well-laid roads with up-to-date infrastructure and lane markings, while the second road network will be an older road with infrastructure and lane markings reflecting the road network's age. The performance of the proposed method will be evaluated on the custom dataset to compare its performance to the BDD100k dataset. In summary, this paper will use Transfer Learning to provide a fast and robust lane detection algorithm that can handle various road conditions and provide accurate lane detection.

Keywords: ADAS, autonomous vehicles, deep learning, LaneNet, lane detection

Procedia PDF Downloads 60

Authors: Jianyong Xue, Olivier L. Georgeon, Salima Hassas

Abstract:

During the initial phase of cognitive development, infants exhibit amazing abilities to generate novel behaviors in unfamiliar situations, and explore actively to learn the best while lacking extrinsic rewards from the environment. These abilities set them apart from even the most advanced autonomous robots. This work seeks to contribute to understand and replicate some of these abilities. We propose the Bottom-up hiErarchical sequential Learning algorithm with Constructivist pAradigm (BEL-CA) to design agents capable of learning autonomously and continuously through interactions. The algorithm implements no assumption about the semantics of input and output data. It does not rely upon a model of the world given a priori in the form of a set of states and transitions as well. Besides, we propose a toolkit to analyze the learning process at run time called GAIT (Generating and Analyzing Interaction Traces). We use GAIT to report and explain the detailed learning process and the structured behaviors that the agent has learned on each decision making. We report an experiment in which the agent learned to successfully interact with its environment and to avoid unfavorable interactions using regularities discovered through interaction.

Keywords: cognitive development, constructivist learning, hierarchical sequential learning, self-adaptation

Procedia PDF Downloads 152

Authors: Sherif Keddis, Mohamed Azzam, Norbert Schwesinger

Abstract:

Harvesting mechanical energy from footsteps or other impacts is a possibility to enable wireless autonomous sensor nodes. These can be used for a highly efficient control of connected devices such as lights, security systems, air conditioning systems or other smart home applications. They can also be used for accurate location or occupancy monitoring. Converting the mechanical energy into useful electrical energy can be achieved using the piezoelectric effect offering simple harvesting setups and low deflections. The challenge facing piezoelectric transducers is the achievable amount of energy per impact in the lower mJ range and the management of such low energies. Simple setups for energy extraction such as a full wave bridge connected directly to a capacitor are problematic due to the mismatch between high impedance sources and low impedance storage elements. Efficient energy circuits for piezoelectric harvesters are commonly designed for vibration harvesters and require periodic input energies with predictable frequencies. Due to the sporadic nature of impact harvesters, such circuits are not well suited. This paper presents a self-powered circuit that avoids the impedance mismatch during energy extraction by disconnecting the load until the source reaches its charge peak. The switch is implemented with passive components and works independent from the input frequency. Therefore, this circuit is suited for impact harvesting and sporadic inputs. For the same input energy, this circuit stores 150% of the energy in comparison to a directly connected capacitor to a bridge rectifier. The total efficiency, defined as the ratio of stored energy on a capacitor to available energy measured across a matched resistive load, is 63%. Although the resulting energy is already sufficient to power certain autonomous applications, further optimization of the circuit are still under investigation in order to improve the overall efficiency.

Keywords: autonomous sensors, circuit design, energy harvesting, energy management, impact harvester, piezoelectricity

Procedia PDF Downloads 121

Authors: Ebasa Girma, Nathnael Minyelshowa, Lebsework Negash

Abstract:

The use of unmanned aerial vehicles (UAVs) in precision agriculture has seen a huge increase recently. As such, systems that aim to apply various algorithms on the field need a structured framework of abstractions. This paper defines the various tasks of the UAVs in precision agriculture and models them into an architectural framework. The presented architecture is built on the context that there will be minimal physical intervention to do the tasks defined with multiple coordinated and cooperative UAVs. Various tasks such as image processing, path planning, communication, data acquisition, and field mapping are employed in the architecture to provide an efficient system. Besides, different limitation for applying Multi-UAVs in precision agriculture has been considered in designing the architecture. The architecture provides an autonomous end-to-end solution, starting from mission planning, data acquisition, and image processing framework that is highly efficient and can enable farmers to comprehensively deploy UAVs onto their lands. Simulation and field tests show that the architecture offers a number of advantages that include fault-tolerance, robustness, developer, and user-friendliness.

Keywords: deep learning, multi-UAVs, precision agriculture, UAVs architecture

Procedia PDF Downloads 89

Authors: Ugur Cihat Sakarya

Abstract:

This research focuses on psychedelic trance music events in Turkey in the context of altered states of consciousness (ASC). The fieldwork that was conducted from 2018 to 2019 is the main source of the research. Participant observation method was followed in 15 selected events. To direct the musical experiences of participants, performances were also presented as a Dj. Ten of these events are open-air festivals. Five of them are indoor parties. The observations made during fieldwork and suitable answers for inference from the interviews with participants, artists, DJs, and volunteers were selected, compiled, and presented. In the result, findings showed that these activities are perceived as temporary autonomous areas by the participants both in time and space and that these activities are suitable areas for expressing themselves as a group (psyfamily) against mainstream culture. It has been observed that the elements that complement the altered states of consciousness in these events are music, visual arts, drug use, and desire to experience spiritual experiences. It is thought that this first academic study -about this topic in Turkey- will open a door for future researches.

Keywords: consciousness, psychedelic, psytrance, rave, Turkey

Procedia PDF Downloads 114

Authors: Moohyun Lee, Soojung Hur, Yongwan Park

Abstract:

In this paper is proposed a method uses only LIDAR system to classification an obstacle and determine its type by establishing database for classifying obstacles based on LIDAR. The existing LIDAR system, in determining the recognition of obstruction in an autonomous vehicle, has an advantage in terms of accuracy and shorter recognition time. However, it was difficult to determine the type of obstacle and therefore accurate path planning based on the type of obstacle was not possible. In order to overcome this problem, a method of classifying obstacle type based on existing LIDAR and using the width of obstacle materials was proposed. However, width measurement was not sufficient to improve accuracy. In this research, the width data was used to do the first classification; database for LIDAR intensity data by four major obstacle materials on the road were created; comparison is made to the LIDAR intensity data of actual obstacle materials; and determine the obstacle type by finding the one with highest similarity values. An experiment using an actual autonomous vehicle under real environment shows that data declined in quality in comparison to 3D LIDAR and it was possible to classify obstacle materials using 2D LIDAR.

Keywords: obstacle, classification, database, LIDAR, segmentation, intensity

Procedia PDF Downloads 311

Authors: Marielcio Lacerda, Angelo Paulino, Elcio Shiguemori, Alvaro Damiao, Lamartine Guimaraes, Camila Anjos

Abstract:

Accurate information about the terrain is extremely important in disaster management activities or conflict. This paper proposes the use of the Unmanned Aircraft Systems (UAS) at the identification of Airdrop Zones (AZs) and Helicopter Landing Zones (HLZs). In this paper we consider the AZs the zones where troops or supplies are dropped by parachute, and HLZs areas where victims can be rescued. The use of digital image processing enables the automatic generation of an orthorectified mosaic and an actual Digital Surface Model (DSM). This methodology allows obtaining this fundamental information to the terrain’s comprehension post-disaster in a short amount of time and with good accuracy. In order to get the identification and classification of AZs and HLZs images from DJI drone, model Phantom 4 have been used. The images were obtained with the knowledge and authorization of the responsible sectors and were duly registered in the control agencies. The flight was performed on May 24, 2017, and approximately 1,300 images were obtained during approximately 1 hour of flight. Afterward, new attributes were generated by Feature Extraction (FE) from the original images. The use of multispectral images and complementary attributes generated independently from them increases the accuracy of classification. The attributes of this work include the Declivity Map and Principal Component Analysis (PCA). For the classification four distinct classes were considered: HLZ 1 – small size (18m x 18m); HLZ 2 – medium size (23m x 23m); HLZ 3 – large size (28m x 28m); AZ (100m x 100m). The Decision Tree method Random Forest (RF) was used in this work. RF is a classification method that uses a large collection of de-correlated decision trees. Different random sets of samples are used as sampled objects. The results of classification from each tree and for each object is called a class vote. The resulting classification is decided by a majority of class votes. In this case, we used 200 trees for the execution of RF in the software WEKA 3.8. The classification result was visualized on QGIS Desktop 2.12.3. Through the methodology used, it was possible to classify in the study area: 6 areas as HLZ 1, 6 areas as HLZ 2, 4 areas as HLZ 3; and 2 areas as AZ. It should be noted that an area classified as AZ covers the classifications of the other classes, and may be used as AZ, HLZ of large size (HLZ3), medium size (HLZ2) and small size helicopters (HLZ1). Likewise, an area classified as HLZ for large rotary wing aircraft (HLZ3) covers the smaller area classifications, and so on. It was concluded that images obtained through small UAV are of great use in calamity situations since they can provide data with high accuracy, with low cost, low risk and ease and agility in obtaining aerial photographs. This allows the generation, in a short time, of information about the features of the terrain in order to serve as an important decision support tool.

Keywords: disaster management, unmanned aircraft systems, helicopter landing zones, airdrop zones, random forest

Procedia PDF Downloads 148

Authors: O. O. Fola-Matthews, O. O. Soyinka, D. N. Bitalo

Abstract:

Nigeria is one of the major shark fishing nations in Africa, but its fisheries managers still record catch data in aggregates ‘sharks’ with no species-specific details. This is because most of the shark specimens look identical in morphology, and field identification of some closely related species is tricky. This study uses DNA barcoding as a method to identify shark species from five different landing areas off the Nigerian Coast. 100 dorsal fins were sampled in order to provide a Chondrichthyan sequence that would be matched to reference specimens in a DNA barcode database

Keywords: BOLD, DNA barcoding, nigeria, sharks

Procedia PDF Downloads 136

Authors: Lucian Stefanita Grigore, Damian Gorgoteanu, Cristian Molder, Amado Stefan, Daniel Constantin

Abstract:

The purpose of this article is to present an analytical-numerical study on the structural behavior of a sunken autonomous underwater vehicle (AUV) for emergency intervention. The need for such a study was generated by the key objective of the ERL-Emergency project. The project aims to develop a system of collaborative robots for emergency response. The system consists of two robots: unmanned ground vehicles (UGV) on tracks and the second is an AUV. The system of collaborative robots, AUV and UGV, will be used to perform missions of monitoring, intervention, and rescue. The main mission of the AUV is to dive into the maritime space of an industrial port to detect possible leaks in a pipeline transporting petroleum products. Another mission is to close and open the valves with which the pipes are provided. Finally, you will need to be able to lift a manikin to the surface, which you can take to land. Numerical analysis was performed by the finite element method (FEM). The conditions for immersing the AUV at 100 m depth were simulated, and the calculations for different fluid flow rates were repeated. From a structural point of view, the stiffening areas and the enclosures in which the command-and-control elements and the accumulators are located have been especially analyzed. The conclusion of this research is that the AUV meets very well the established requirements.

Keywords: analytical-numerical, emergency, FEM, robotics, underwater

Procedia PDF Downloads 123

Authors: Tao Song, Hao Cheng, Guangfeng Tian, Chuang Xu

Abstract:

An autonomous emergency braking system is an advanced driving assistance system that enables vehicle collision avoidance and pedestrian collision avoidance to improve vehicle safety. At present, because the pedestrian target is small, and the mobility is large, the pedestrian AEB system is faced with more technical difficulties and higher functional requirements. In this paper, a method of pedestrian target selection based on a variable width funnel is proposed. Based on the current position and predicted position of pedestrians, the relative position of vehicle and pedestrian at the time of collision is calculated, and different braking strategies are adopted according to the hazard level of pedestrian collisions. In the CNCAP standard operating conditions, comparing the method of considering only the current position of pedestrians and the method of considering pedestrian prediction position, as well as the method based on fixed width funnel and variable width funnel, the results show that, based on variable width funnel, the choice of pedestrian target will be more accurate and the opportunity of the intervention of AEB system will be more reasonable by considering the predicted position of the pedestrian target and vehicle's lateral motion.

Keywords: automatic emergency braking system, pedestrian target selection, TTC, variable width funnel

Procedia PDF Downloads 131

Authors: Mannika Garg, N. Srinivas Murthy, Sunish Nair

Abstract:

TeamIndus is only Indian team participated in the Google Lunar X Prize (GLXP). GLXP is an incentive prize space competition which is organized by the XPrize Foundation and sponsored by Google. The main objective of the mission is to soft land a rover on the moon surface, travel minimum displacement of 500 meters and transmit HD and NRT videos and images to the Earth. Team Indus is designing a Lunar Lander which carries Rover with it and deliver onto the surface of the moon with a soft landing. For lander to survive throughout the mission, energy is required to operate all attitude control sensors, actuators, heaters and other necessary components. Photovoltaic solar array systems are the most common and primary source of power generation for any spacecraft. The scope of this paper is to provide a system-level approach for designing the solar array systems of the lander to generate required power to accomplish the mission. For this mission, the direction of design effort is to higher efficiency, high reliability and high specific power. Towards this approach, highly efficient multi-junction cells have been considered. The design is influenced by other constraints also like; mission profile, chosen spacecraft attitude, overall lander configuration, cost effectiveness and sizing requirements. This paper also addresses the various solar array design challenges such as operating temperature, shadowing, radiation environment and mission life and strategy of supporting required power levels (peak and average). The challenge to generate sufficient power at the time of surface touchdown, due to low sun elevation (El) and azimuth (Az) angle which depends on Lunar landing site, has also been showcased in this paper. To achieve this goal, energy balance analysis has been carried out to study the impact of the above-mentioned factors and to meet the requirements and has been discussed in this paper.

Keywords: energy balance analysis, multi junction solar cells, photovoltaic, reliability, spacecraft attitude

Procedia PDF Downloads 205

Authors: Ahmad Fakhriy Hassan, Rohani Ahmad, Zurainee Mohamed Nor, Wan Najdah Wan Mohamad Ali

Abstract:

In Malaysia, it was realized that while the incidence of human malaria is decreasing, the incidence of Plasmodium knowlesi malaria appears to be on the rise, especially in rural areas of Sabah, East Malaysia. The primary vector for P. knowlesi malaria in Sabah is An. balabacensis a species found abundant in rural areas, shown to rest and feed outdoor throughout the night, which makes its control very challenging. This study aims to examine the distribution of malaria-infected Anopheles mosquitoes in three areas in Sabah, namely Kudat, Ranau, and Tenom, known as areas in Sabah that presented high number of malaria cases. Briefly, mosquitoes were caught every 6 weeks for the period of 18 months using Human Landing Catching (HLC) technique from May 2016 to November 2017. Identification of species was done using microscopy and molecular methods. Molecular method is also used to detect malaria parasite in all mosquito collected. An. balabacensis was present in all the study areas. In Kudat, six other Anopheles species were also detected, namely, An. barumbrosus, An. latens, An. letifer, An. maculatus, An. sundaicus and An. tesselatus. In Ranau five other Anopheles species were detected, namely, An. barumbrosus, An. donaldi., An. hodgkini, An. maculatus, and An. tesselatus while in Tenom seven more species An. donaldi, An. umbrosus, An. barumbrosus, An.latens, An. hodgkini, An. maculatus, and An. tesselatus were detected. This study showed 24% out of 259, 39% out of 127, and 26% out of 265 Anopheles mosquito collected in Kudat, Ranau, and Tenom were detected positive for malaria parasite respectively. In Kudat An. balabacensis, An. barumbrosus, An. latens, An. maculatus, An. sundaicus and An. tesselatus were the six out of eight Anopheles species that were found infected with malaria parasite. All Anopheles species collected in Ranau were positive for malaria while In Tenom, only five out of eight species; An. balabacensus, An. donaldi, An. hodgkini, An. maculatus, and An. latens were detected positive for malaria parasite. Interestingly, for all study areas An. balabacensis was shown to be the only species infected with four malaria species; P. falciparum, P. knowlesi, P. vivax, and Plasmodium sp. This finding clearly indicates that An. balabacensis is the dominant malaria vector in Kudat, Ranau, and Tenom.

Keywords: Anopheles balabacensis, human landing catching technique, nested PCR, Plasmodium knowlesi, Simian malaria

Procedia PDF Downloads 113

Authors: Arne Hitzmann, Philipp Wentscher, Alexander Gabel, Reinhard Gerndt

Abstract:

Autonomous mobile robots can be found in a wide field of applications. Their types range from household robots over workshop robots to autonomous cars and many more. All of them undergo a number of testing steps during development, production and maintenance. This paper describes an approach to improve testing of robot behavior. It was inspired by the RoboCup @work competition that itself reflects a robotics benchmark for industrial robotics. There, scaled down versions of mobile industrial robots have to navigate through a workshop-like environment or operation area and have to perform tasks of manipulating and transporting work pieces. This paper will introduce an approach of automated vision-based testing of the behavior of the so called youBot robot, which is the most widely used robot platform in the RoboCup @work competition. The proposed system allows automated testing of multiple tries of the robot to perform a specific missions and it allows for the flexibility of the robot, e.g. selecting different paths between two tasks within a mission. The approach is based on a multi-camera setup using, off the shelf cameras and optical markers. It has been applied for test-driven development (TDD) and maintenance-like verification of the robot behavior and performance.

Keywords: supervisory control, testing, markers, mono vision, automation

Procedia PDF Downloads 354

Authors: Nayden Chivarov, Denis Chikurtev, Kaloyan Yovchev, Nedko Shivarov

Abstract:

This paper represents methods for improving the efficiency and precision of service mobile robot. This robot is used for increasing the quality of life of elderly and disabled people. The key concept of the proposed Intelligent Service Mobile Robot is its easier adaptability to achieve services for a wide range of Elderly or Disabled Person’s needs, by performing different tasks for supporting Elderly or Disabled Persons care. We developed robot autonomous navigation and computer vision systems in order to recognize different objects and bring them to the people. Web based user interface is developed to provide easy access and tele-control of the robot by any device through the internet. In this study algorithms for object recognition and localization are proposed for providing successful object recognition and accuracy in the positioning. Different methods for sending movement commands to the mobile robot system are proposed and evaluated. After executing some experiments to show the results of the research, we can summarize that these systems and algorithms provide good control of the service mobile robot and it will be more useful to help the elderly and disabled persons.

Keywords: service robot, mobile robot, autonomous navigation, computer vision, web user interface, ROS

Procedia PDF Downloads 312

Authors: M. S. Nikitenko, S. A. Kizilov, D. Y. Khudonogov

Abstract:

The paper considers an approach to a machine vision operating system combined with using a grid of light markers. This approach is used to solve several scientific and technical problems, such as measuring the capability of an apron feeder delivering coal from a lining return port to a conveyor in the technology of mining high coal releasing to a conveyor and prototyping an autonomous vehicle obstacle detection system. Primary verification of a method of calculating bulk material volume using three-dimensional modeling and validation in laboratory conditions with relative errors calculation were carried out. A method of calculating the capability of an apron feeder based on a machine vision system and a simplifying technology of a three-dimensional modelled examined measuring area with machine vision was offered. The proposed method allows measuring the volume of rock mass moved by an apron feeder using machine vision. This approach solves the volume control issue of coal produced by a feeder while working off high coal by lava complexes with release to a conveyor with accuracy applied for practical application. The developed mathematical apparatus for measuring feeder productivity in kg/s uses only basic mathematical functions such as addition, subtraction, multiplication, and division. Thus, this fact simplifies software development, and this fact expands the variety of microcontrollers and microcomputers suitable for performing tasks of calculating feeder capability. A feature of an obstacle detection issue is to correct distortions of the laser grid, which simplifies their detection. The paper presents algorithms for video camera image processing and autonomous vehicle model control based on obstacle detection machine vision systems. A sample fragment of obstacle detection at the moment of distortion with the laser grid is demonstrated.

Keywords: machine vision, machine vision operating system, light markers, measuring capability, obstacle detection system, autonomous transport

Procedia PDF Downloads 83

Authors: Nicholas Lambert, Seungyeon Ryu, Mehmet Mulla, Albert Kim

Abstract:

In this paper, an interactive in-car interface called HoloDash is presented. It is intended to provide information and infotainment in both autonomous vehicles and ‘connected cars’, vehicles equipped with Internet access via cellular services. The research focuses on the development of interactive avatars for this system and its gesture-based control system. This is a case study for the development of a possible human-centred means of presenting a connected or autonomous vehicle’s On-Board Diagnostics through a projected ‘holographic’ infotainment system. This system is termed a Holographic Human Vehicle Interface (HHIV), as it utilises a dashboard projection unit and gesture detection. The research also examines the suitability for gestures in an automotive environment, given that it might be used in both driver-controlled and driverless vehicles. Using Human Centred Design methods, questions were posed to test subjects and preferences discovered in terms of the gesture interface and the user experience for passengers within the vehicle. These affirm the benefits of this mode of visual communication for both connected and driverless cars.

Keywords: gesture, holographic interface, human-computer interaction, user-centered design

Procedia PDF Downloads 286

Authors: Wiem Zemzem, Moncef Tagina

Abstract:

In this work, we are addressing the problem of an autonomous mobile robot navigating in a large, unknown and dynamic environment using reinforcement learning abilities. This problem is principally related to the exploration/exploitation dilemma, especially the need to find a solution letting the robot detect the environmental change and also learn in order to adapt to the new environmental form without ignoring knowledge already acquired. Firstly, a new action selection strategy, called ε-greedy-MPA (the ε-greedy policy favoring the most promising actions) is proposed. Unlike existing exploration/exploitation policies (EEPs) such as ε-greedy and Boltzmann, the new EEP doesn’t only rely on the information of the actual state but also uses those of the eventual next states. Secondly, as the environment is large, an exploration favoring least recently visited states is added to the proposed EEP in order to accelerate learning. Finally, various simulations with ball-catching problem have been conducted to evaluate the ε-greedy-MPA policy. The results of simulated experiments show that combining this policy with the Qlearning method is more effective and efficient compared with the ε-greedy policy in stationary environments and the utility-based reinforcement learning approach in non stationary environments.

Keywords: autonomous mobile robot, exploration/ exploitation policy, large, dynamic environment, reinforcement learning

Procedia PDF Downloads 386

Authors: Robson C. Santos, Julio C. P. Ribeiro, Iorran M. de Castro, Luan C. F. Rodrigues, Sandro R. L. Silva, Diego M. Quesada

Abstract:

The work aims to develop a robot in the form of autonomous vehicle to detect, inspection and mapping of underground pipelines through the ATmega328 Arduino platform. Hardware prototyping very similar to C / C ++ language that facilitates its use in robotics open source, resembles PLC used in large industrial processes. The robot will traverse the surface independently of direct human action, in order to automate the process of detecting buried pipes, guided by electromagnetic induction. The induction comes from coils that sends the signal to the Arduino microcontroller contained in that will make the difference in intensity and the treatment of the information, then this determines actions to electrical components such as relays and motors, allowing the prototype to move on the surface and getting the necessary information. The robot was developed by electrical and electronic assemblies that allowed test your application. The assembly is made up of metal detector coils, circuit boards and microprocessor, which interconnected circuits previously developed can determine, process control and mechanical actions for a robot (autonomous car) that will make the detection and mapping of buried pipelines plates.

Keywords: robotic, metal detector, embedded system, pipeline inspection

Procedia PDF Downloads 590

Authors: Mirza Mujtaba Baig

Abstract:

Artificial Intelligence (AI) is evolving rapidly, and one of the areas in which this field has influenced is automation. The automobile, healthcare, education, and robotic industries deploy AI technologies constantly, and the automation of tasks is beneficial to allow time for knowledge-based tasks and also introduce convenience to everyday human endeavors. The paper reviews the challenges faced with the current implementations of autonomous self-driving cars by exploring the machine learning, robotics, and artificial intelligence techniques employed for the development of this innovation. The controversy surrounding the development and deployment of autonomous machines, e.g., vehicles, begs the need for the exploration of the configuration of the programming modules. This paper seeks to add to the body of knowledge of research assisting researchers in decreasing the inconsistencies in current programming modules. Blockchain is a technology of which applications are mostly found within the domains of financial, pharmaceutical, manufacturing, and artificial intelligence. The registering of events in a secured manner as well as applying external algorithms required for the data analytics are especially helpful for integrating, adapting, maintaining, and extending to new domains, especially predictive analytics applications.

Keywords: artificial intelligence, automation, big data, self-driving cars, machine learning, neural networking algorithm, blockchain, business intelligence

Procedia PDF Downloads 89

Authors: Zamri Omar, Alifi Zainal Abidin

Abstract:

Although flying machines have made their tremendous technological advancement since the first successfully flight of the heavier-than-air aircraft, its benefits to the greater community are still belittled. One of the reasons for this drawback is due to the relatively high cost needed to fly on the typical light aircraft. A smaller and lighter plane, widely known as Light Sport Aircraft (LSA) has the potential to attract more people to actively participate in numerous flying activities, such as for recreational, business trips or other personal purposes. In this paper, we propose a new LSA design with some simple, yet important analysis required in the aircraft conceptual design stage.

Keywords: light sport aircraft, conceptual design, aircraft layout, aircraft

Procedia PDF Downloads 314

Authors: Phillip Garrad, Saritha Unnikrishnan

Abstract:

The recent popularity of connected and autonomous vehicles (CAV) corresponds with an increase in the risk of cyber-attacks. These cyber-attacks have been instigated by both researchers or white-coat hackers and cyber-criminals. As Connected Vehicles move towards full autonomy, the impact of these cyber-attacks also grows. The current research details challenges faced in cybersecurity testing of CAV, including access and cost of the representative test setup. Other challenges faced are lack of experts in the field. Possible solutions to how these challenges can be overcome are reviewed and discussed. From these findings, a software simulated CAV network is established as a cost-effective representative testbed. Penetration tests are then performed on this simulation, demonstrating a cyber-attack in CAV. Studies have shown Artificial Intelligence (AI) to improve runtime, increase efficiency and comprehensively cover all the typical test aspects in penetration testing in other industries. There is an attempt to introduce similar AI models to the software simulation. The expectation from this implementation is to see similar improvements in runtime and efficiency for the CAV model. If proven to be an effective means of penetration test for CAV, this methodology may be used on a full CAV test network.

Keywords: cybersecurity, connected vehicles, software simulation, artificial intelligence, penetration testing

Procedia PDF Downloads 78