6 research outputs found

    Transmission line inspection using suspended robot: Cost effective analysis and operational routing identification

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    High voltage transmission lines form a crucial part of the energy infrastructure of a country. Effective maintenance is required to maintain its reliability and reduce the probability of the occurrence of the outage. Conventionally, the routine inspection of the transmission line was conducted by linemen with the assistance of hot stick and helicopter, which is considered dangerous, time-consuming, and expensive. In this thesis, we focus on the initial study of seeking the state of the art robotics technology to by largely replace human beings in transmission line inspection. The existing robotics technologies that are interested by utility companies, as well as the background information of transmission system, are first briefly reviewed. The motivation and objective of the thesis are given. Then, a cost model for using a suspended robot in transmission line inspection following a heuristic routing strategy that guides the motion of the ground support team is introduced. Numerical case study considering various terrain characteristics is implemented to demonstrate the cost related performance of the inspection task using the suspended robot. After that, a revised A-Star routing algorithm is derived to identify the travel path of the ground team to reduce the travel time and distance to further improve the cost-effectiveness of using the suspended robot in transmission line inspection. A true segment of transmission line in Missouri (MO) is used in case study to illustrate the effectiveness of the derived routing algorithm. Finally, the conclusion of the thesis is drawn, and the future work is discussed --Abstract, page iii

    A Power Line Inspector Device

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    The goal of this project is to create a functional power line inspection device which could replace the old inspection method of using helicopters. This microchip based robotic device is able to ride along a conductor and send video feed, encoder readouts, and temperature measurements to the user. The user operating system consists of an LCD screen, two potentiometers for motor control, and a screen to display video feed. Achieved specifications include a battery lifetime of 1 hour and 45 minutes, distance measurements within 1 inch, and temperature accuracy within 2 °C. This thesis includes a brief discussion on previous methods and robots, theory of operation, design summaries, and a compilation of the final results

    Routing algorithm for the ground team in transmission line inspection using unmanned aerial vehicle

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    With the rapid development of robotics technology, robots are increasingly used to conduct various tasks by utility companies. An unmanned aerial vehicle (UAV) is an efficient robot that can be used to inspect high-voltage transmission lines. UAVs need to stay within a data transmission range from the ground station and periodically land to replace the battery in order to ensure that the power system can support its operation. A routing algorithm must be used in order to guide the motion and deployment of the ground station while using UAV in transmission line inspection. Most existing routing algorithms are dedicated to pathfinding for a single object that needs to travel from a given start point to end point and cannot be directly used for guiding the ground station deployment and motion since multiple objects (i.e., the UAV and the ground team) whose motions and locations need to be coordinated are involved. In this thesis, we intend to explore the routing algorithm that can be used by utility companies to effectively utilize UAVs in transmission line inspection. Both heuristic and analytical algorithms are proposed to guide the deployment of the ground station and the landing point for UAV power system change. A case study was conducted to validate the effectiveness of the proposed routing algorithm and examine the performance and cost-effectiveness --Abstract, page iii

    Vision-Based Control of Unmanned Aerial Vehicles for Automated Structural Monitoring and Geo-Structural Analysis of Civil Infrastructure Systems

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    The emergence of wireless sensors capable of sensing, embedded computing, and wireless communication has provided an affordable means of monitoring large-scale civil infrastructure systems with ease. To date, the majority of the existing monitoring systems, including those based on wireless sensors, are stationary with measurement nodes installed without an intention for relocation later. Many monitoring applications involving structural and geotechnical systems require a high density of sensors to provide sufficient spatial resolution to their assessment of system performance. While wireless sensors have made high density monitoring systems possible, an alternative approach would be to empower the mobility of the sensors themselves to transform wireless sensor networks (WSNs) into mobile sensor networks (MSNs). In doing so, many benefits would be derived including reducing the total number of sensors needed while introducing the ability to learn from the data obtained to improve the location of sensors installed. One approach to achieving MSNs is to integrate the use of unmanned aerial vehicles (UAVs) into the monitoring application. UAV-based MSNs have the potential to transform current monitoring practices by improving the speed and quality of data collected while reducing overall system costs. The efforts of this study have been chiefly focused upon using autonomous UAVs to deploy, operate, and reconfigure MSNs in a fully autonomous manner for field monitoring of civil infrastructure systems. This study aims to overcome two main challenges pertaining to UAV-enabled wireless monitoring: the need for high-precision localization methods for outdoor UAV navigation and facilitating modes of direct interaction between UAVs and their built or natural environments. A vision-aided UAV positioning algorithm is first introduced to augment traditional inertial sensing techniques to enhance the ability of UAVs to accurately localize themselves in a civil infrastructure system for placement of wireless sensors. Multi-resolution fiducial markers indicating sensor placement locations are applied to the surface of a structure, serving as navigation guides and precision landing targets for a UAV carrying a wireless sensor. Visual-inertial fusion is implemented via a discrete-time Kalman filter to further increase the robustness of the relative position estimation algorithm resulting in localization accuracies of 10 cm or smaller. The precision landing of UAVs that allows the MSN topology change is validated on a simple beam with the UAV-based MSN collecting ambient response data for extraction of global mode shapes of the structure. The work also explores the integration of a magnetic gripper with a UAV to drop defined weights from an elevation to provide a high energy seismic source for MSNs engaged in seismic monitoring applications. Leveraging tailored visual detection and precise position control techniques for UAVs, the work illustrates the ability of UAVs to—in a repeated and autonomous fashion—deploy wireless geophones and to introduce an impulsive seismic source for in situ shear wave velocity profiling using the spectral analysis of surface waves (SASW) method. The dispersion curve of the shear wave profile of the geotechnical system is shown nearly equal between the autonomous UAV-based MSN architecture and that taken by a traditional wired and manually operated SASW data collection system. The developments and proof-of-concept systems advanced in this study will extend the body of knowledge of robot-deployed MSN with the hope of extending the capabilities of monitoring systems while eradicating the need for human interventions in their design and use.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169980/1/zhh_1.pd

    Motion Planning

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    Motion planning is a fundamental function in robotics and numerous intelligent machines. The global concept of planning involves multiple capabilities, such as path generation, dynamic planning, optimization, tracking, and control. This book has organized different planning topics into three general perspectives that are classified by the type of robotic applications. The chapters are a selection of recent developments in a) planning and tracking methods for unmanned aerial vehicles, b) heuristically based methods for navigation planning and routes optimization, and c) control techniques developed for path planning of autonomous wheeled platforms
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