33 research outputs found

    Outdoor navigation of mobile robots

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    AGVs in the manufacturing industry currently constitute the largest application area for mobile robots. Other applications have been gradually emerging, including various transporting tasks in demanding environments, such as mines or harbours. Most of the new potential applications require a free-ranging navigation system, which means that the path of a robot is no longer bound to follow a buried inductive cable. Moreover, changing the route of a robot or taking a new working area into use must be as effective as possible. These requirements set new challenges for the navigation systems of mobile robots. One of the basic methods of building a free ranging navigation system is to combine dead reckoning navigation with the detection of beacons at known locations. This approach is the backbone of the navigation systems in this study. The study describes research and development work in the area of mobile robotics including the applications in forestry, agriculture, mining, and transportation in a factory yard. The focus is on describing navigation sensors and methods for position and heading estimation by fusing dead reckoning and beacon detection information. A Kalman filter is typically used here for sensor fusion. Both cases of using either artificial or natural beacons have been covered. Artificial beacons used in the research and development projects include specially designed flat objects to be detected using a camera as the detection sensor, GPS satellite positioning system, and passive transponders buried in the ground along the route of a robot. The walls in a mine tunnel have been used as natural beacons. In this case, special attention has been paid to map building and using the map for positioning. The main contribution of the study is in describing the structure of a working navigation system, including positioning and position control. The navigation system for mining application, in particular, contains some unique features that provide an easy-to-use procedure for taking new production areas into use and making it possible to drive a heavy mining machine autonomously at speed comparable to an experienced human driver.reviewe

    DEVELOPMENT OF AN AUTONOMOUS NAVIGATION SYSTEM FOR THE SHUTTLE CAR IN UNDERGROUND ROOM & PILLAR COAL MINES

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    In recent years, autonomous solutions in the multi-disciplinary field of the mining engineering have been an extremely popular applied research topic. The growing demand for mineral supplies combined with the steady decline in the available surface reserves has driven the mining industry to mine deeper underground deposits. These deposits are difficult to access, and the environment may be hazardous to mine personnel (e.g., increased heat, difficult ventilation conditions, etc.). Moreover, current mining methods expose the miners to numerous occupational hazards such as working in the proximity of heavy mining equipment, possible roof falls, as well as noise and dust. As a result, the mining industry, in its efforts to modernize and advance its methods and techniques, is one of the many industries that has turned to autonomous systems. Vehicle automation in such complex working environments can play a critical role in improving worker safety and mine productivity. One of the most time-consuming tasks of the mining cycle is the transportation of the extracted ore from the face to the main haulage facility or to surface processing facilities. Although conveyor belts have long been the autonomous transportation means of choice, there are still many cases where a discrete transportation system is needed to transport materials from the face to the main haulage system. The current dissertation presents the development of a navigation system for an autonomous shuttle car (ASC) in underground room and pillar coal mines. By introducing autonomous shuttle cars, the operator can be relocated from the dusty, noisy, and potentially dangerous environment of the underground mine to the safer location of a control room. This dissertation focuses on the development and testing of an autonomous navigation system for an underground room and pillar coal mine. A simplified relative localization system which determines the location of the vehicle relatively to salient features derived from on-board 2D LiDAR scans was developed for a semi-autonomous laboratory-scale shuttle car prototype. This simplified relative localization system is heavily dependent on and at the same time leverages the room and pillar geometry. Instead of keeping track of a global position of the vehicle relatively to a fixed coordinates frame, the proposed custom localization technique requires information regarding only the immediate surroundings. The followed approach enables the prototype to navigate around the pillars in real-time using a deterministic Finite-State Machine which models the behavior of the vehicle in the room and pillar mine with only a few states. Also, a user centered GUI has been developed that allows for a human user to control and monitor the autonomous vehicle by implementing the proposed navigation system. Experimental tests have been conducted in a mock mine in order to evaluate the performance of the developed system. A number of different scenarios simulating common missions that a shuttle car needs to undertake in a room and pillar mine. The results show a minimum success ratio of 70%

    Modelling and control of an autonomous underground mine vehicle

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    The mining industry is constantly under pressure to improve productivity, effciency and safety. Although an increased use of automation technology has the potential of con- tributing to improvements in all three factors mines have been relatively slow to make use of automation technology. Automation in the underground mining environment is a challenging prospect for a number of reasons not least of which being the diffculties and associated costs of installing infrastructure in this hazardous environment. The work described in this dissertation focuses on the modelling of a Load-Haul-Dump or LHD vehicle for the purpose of autonomous navigation and control. Considerable progress has been made in automating underground mining vehicles in recent years, and successful test installations have been made. There are still however a number of shortcomings in the existing autonomous underground mine vehicle navigation systems. This dissertation attempts to address some of these problems through the development of a more accurate vehicle model for an LHD vehicle incorporating some vehicle and tyre dynamics thereby potentially reducing the number of sensors and the amount of installed infrastructure necessary to implement the vehicle navigation system. Simulation results are provided for different vehicle modelling techniques and the results are compared and discussed in terms of their suitability for physical implementation in an underground mine.Dissertation (MEng (Electronic Engineering))--University of Pretoria, 2007.Electrical, Electronic and Computer EngineeringMEngunrestricte

    Controlling a Fleet of Autonomous LHD Vehicles in Mining Operation

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    In this chapter, we report on our activities to create and maintain a fleet of autonomous load haul dump (LHD) vehicles for mining operations. The ever increasing demand for sustainable solutions and economic pressure causes innovation in the mining industry just like in any other branch. In this chapter, we present our approach to create a fleet of autonomous special purpose vehicles and to control these vehicles in mining operations. After an initial exploration of the site we deploy the fleet. Every vehicle is running an instance of our ROS 2-based architecture. The fleet is then controlled with a dedicated planning module. We also use continuous environment monitoring to implement a life-long mapping approach. In our experiments, we show that a combination of synthetic, augmented and real training data improves our classifier based on the deep learning network Yolo v5 to detect our vehicles, persons and navigation beacons. The classifier was successfully installed on the NVidia AGX-Drive platform, so that the abovementioned objects can be recognised during the dumper drive. The 3D poses of the detected beacons are assigned to lanelets and transferred to an existing map

    Modelling and control of an articulated underground mining vehicle

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    The automation of the tramming or load, haul and dump (LHD) procedure, performed by a LHD vehicle, holds the potential to improve productivity, efficiency and safety in the mining environment. Productivity is mainly increased by longer working hours; efficiency is improved by repetitive, faultless and predictable work; and safety is improved by removing the human operator from the harsh environment. However, before the automation of the process can be addressed, a thorough understanding of the process and its duty in the overall mining method is required. Therefore, the current applicable mining methods and their areas of potential automation are given. Since the automation of the LHD vehicle is at the core of this project, its implementation in the tramming process is also justified. Also, the current underground navigation methods are given and their shortcomings are named. It is concluded that infrastructure-free navigation is the only viable solution in the ever-changing mining environment. With that in mind, the feasibility of various navigation sensors is discussed and conclusions are drawn. Both kinematic and dynamic modelling of LHD vehicles are introduced. Various forms of kinematic models are given and their underlying modelling assumptions are named. The most prominent assumptions concern the vehicle’s half-length and the inclusion of a wheel-slip factor. Dynamic modelling techniques, with a strong emphasis on tyre modelling, are also stated. In order to evaluate the modelling techniques, field tests are performed on the articulated vehicles, namely the Wright 365 LHD and the Bell 1706C loader. The test on the Wright 365 LHD gives a good impression of the harsh ergonomics under which the operator has to work. A more thorough test is performed on the Bell 1706C articulated loader. The test results are then compared to simulation results obtained from the kinematic models. Also, the above-named assumptions are tested, evaluated and discussed. A dynamic model is also simulated and discussed. Lastly, two localization and control methods are given and evaluated. The first method is an open-loop nonlinear optimal control strategy with periodic position resetting and the second method is a pathtracking controller. AFRIKAANS : Automatisering van die laai-, vervoer- en dompel- (LVD) prosedure het die potensiaal om die produktiwiteit, effektiwiteit en veiligheid van die mynbedryf te verbeter. Produktiwiteit word hoofsaaklik deur langer werksure verhoog, effektiwiteit word deur herhalende, foutlose en voorspelbare werk verbeter en veiligheid word verbeter omdat menslike operateurs uit die gevaarlike ondergrondse omgewing verwyder word. Voordat aandag aan die automatisering van die prosedure geskenk kan word, moet die prosedure en die algemene mynbedrywighede rakende die prosedure deeglik bestudeer en verstaan word. As gevolg hiervan word die huidige, toepaslike mynboumetodes hier gedokumenteer. Die implementering van ʼn gekoppelde LVD-voertuig in die LVD-prosesword ook geregverdig. Verder word die huidige metodes van ondergrondse navigasie genoem en hulle tekortkominge aangedui. Die gevolgtrekking dat infrastruktuur-vrye navigasie die enigste lewensvatbare navigasiemetode in die immer veranderende ondergrondsemynbouomgewing is, word ook gemaak. In die lig daarvan word ʼn verskeidenheid sensors genoem en bespreek. Kinematiese en dinamiese modellering van ʼn LVD-voertuig word bekendgestel. Verskeie kinematiese modelle en hulle onderliggende aannames word genoem. Die mees prominente aannames is die lengte van die gekoppelde voertuig se hoofdele en die insluiting van ʼn wielglipfaktor. Die tegnieke van dinamiese modellering, met die klem op bandmodellering, word ook gegee. Praktyktoetse op gekoppelde voertuie is ook gedoen om die verskillende modelle te evalueer. Die toets op die Wright 365-LVD bied goeie insig in die strawwe ergonomiese toestande waaronder die operateurs moet werk. ʼn Deeglike toets is op ʼn BELL 1706C- gekoppelde laaier, wat kinematies identies aan ʼn LVD-voertuig is, uitgevoer. Die bevindinge van die toets word met bogenoemde modelsimulasies vergelyk en gevolgtrekkings word gemaak. Laastens word lokalisiering en beheer van ʼn LVDvoertuig behandel. Twee beheermetodes, opelus- nie-lineêre optimale beheer met periodieke herstel en padvolgingbeheer word geëvalueer en bespreek. CopyrightDissertation (MEng)--University of Pretoria, 2012.Electrical, Electronic and Computer Engineeringunrestricte

    Autonomiset työkoneet ja autonomian vaikutus koneturvallisuuteen

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    Autonomous machines and vehicles are an increasing part of everyday life and industrial operations. These machines and vehicles have enjoyed rapid technological advancements in recent years, which has led to increasingly sophisticated functions and functionalities. The advancements in autonomous technologies have, however, given rise to questions and concerns relating to the safety of these machines and vehicles, and on how an adequate level of safety can be ensured when no dedicated operator or driver is present. This thesis looks at the main areas that affect the overall safety of autonomous industrial machines and civilian road vehicles, and presents the most prominent challenges faced in ensuring the safety of autonomous applications. The goal of the thesis is to give the reader an overview of the safety-related aspects of autonomy and to show what has to be considered when ensuring an adequate level of safety for autonomous machines or vehicles. This is achieved by an extensive literature review on autonomous applications in both industrial and automotive fields, and on the safety-related aspects of autonomy. Additionally, mining is used in the thesis as an example of autonomous machines in practice and on the challenges autonomy can face in industrial operations. Based on the research carried out, it can be said that the overall safety of machine autonomy is currently hindered by two main aspects: the lack of applicable standards, legislation and guidelines regarding the autonomy of machines and vehicles, and the paradox that arises from balancing the desired level of autonomy with the needed level of safety. This has led to a situation where, in theory, highly complex and sophisticated autonomous machines are possible from a technical standpoint, but they lack a common and thorough method for ensuring an adequate level of safety

    Data Management System for a Semiautonomous Shuttle Car for Underground Room and Pillar Coal Mines

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    In recent years, autonomous solutions in the multidisciplinary field of mining engineering have been an extremely popular applied research topic. This is a result of the increasing demands of society on mineral resources along with the accelerating exploitation of the currently economically viable resources, which lead the mining sector to turn to deeper, more-difficult-to-mine orebodies. An appropriate data management system comprises a crucial aspect of the designing and the engineering of a system that involves autonomous or semiautonomous vehicles. The vast volume of data collected from onboard sensors, as well as from a potential IoT network dispersed around a smart mine, necessitates the development of a reliable data management strategy. Ideally, this strategy will allow for fast and asynchronous access to the data for real-time processing and decision-making purposes as well as for visualization through a corresponding human–machine interface. The proposed system has been developed for autonomous navigation of a coalmine shuttle car and has been implemented on a 1/6th scale shuttle car in a mock mine. It comprises three separate nodes, namely, a data collection node, a data management node, and a data processing and visualization node. This approach was dictated by the large amount of collected data and the need to ensure uninterrupted and fast data management and flow. The implementation of an SQL database server allows for asynchronous, real-time, and reliable data management, including data storage and retrieval. On the other hand, this approach introduces latencies between the data management node and the other two nodes. In general, these latencies include sensor latencies, network latencies, and processing latencies. However, the data processing and visualization module is able to retrieve and process the latest data and make a decision about the next optimal movement of the shuttle car prototype in less than 900 ms. This allows the prototype to navigate efficiently around the pillars without interruptions

    From teleoperation to the cognitive human-robot interface

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    Robots are slowly moving from factories to mines, construction sites, public places and homes. This new type of robot or robotized working machine – field and service robots (FSR) – should be capable of performing different kinds of tasks in unstructured changing environments, not only among humans but through continuous interaction with humans. The main requirements for an FSR are mobility, advanced perception capabilities, high "intelligence" and easy interaction with humans. Although mobility and perception capabilities are no longer bottlenecks, they can nevertheless still be greatly improved. The main bottlenecks are intelligence and the human - robot interface (HRI). Despite huge efforts in "artificial intelligence" research, the robots and computers are still very "stupid" and there are no major advancements on the horizon. This emphasizes the importance of the HRI. In the subtasks, where high-level cognition or intelligence is needed, the robot has to ask for help from the operator. In addition to task commands and supervision, the HRI has to provide the possibility of exchanging information about the task and environment through continuous dialogue and even methods for direct teleoperation. The thesis describes the development from teleoperation to service robot interfaces and analyses the usability aspects of both teleoperation/telepresence systems and robot interfaces based on high-level cognitive interaction. The analogue in the development of teleoperation interfaces and HRIs is also pointed out. The teleoperation and telepresence interfaces are studied on the basis of a set of experiments in which the different enhancement-level telepresence systems were tested in different tasks of a driving type. The study is concluded by comparing the usability aspects and the feeling of presence in a telepresence system. HRIs are studied with an experimental service robot WorkPartner. Different kinds of direct teleoperation, dialogue and spatial information interfaces are presented and tested. The concepts of cognitive interface and common presence are presented. Finally, the usability aspects of a human service robot interface are discussed and evaluated.reviewe

    Sensors Utilisation and Data Collection of Underground Mining

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    This study reviews IMU significance and performance for underground mine drone localisation. This research has designed a Kalman filter which extracts reliable information from raw data. Kalman filter for INS combines different measurements considering estimated errors to produce a trajectory including time, position and attitude. To evaluate the feasibility of the proposed method, a prototype has been designed and evaluated. Experimental results indicate that the designed Kalman filter estimates the internal states of a system
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