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This paper aims to develop a robot for tightening charged bolt to solve the shortcomings of high labor intensity, low efficiency, high risk and poor reliability in artificially tightening drainage board bolt of strain clamp for high voltage transmission line. Realizing bolt-nut capture and location by manipulator is a critical process to complete the whole working task. To solve such key technology, an autonomous location control method for N-joint robot manipulator based on kinematics was proposed.

Through D-H kinematics analysis under flexible working environment of transmission line, the autonomous location control of double manipulators can be abstracted as a nonlinear approximation problem based on joint inverse kinematics. In addition, regarding the complex coupling relationship among different joint angles and the complex decoupling process which leads to the non-uniqueness of inverse solution, an improved backpropagation (BP) network was proposed based on the combination of dynamic adaptive adjustment of learning rate and variable momentum factor, so that the inverse kinematics of manipulator can be solved and the optimization evaluation mechanism of inverse solution can be presented. The proposed autonomous location control method is of adaptability to flexible environment and structural parameters of different drainage boards. The simulation results verified the effectiveness of the proposed method. Compared with the other location control, this method can achieve faster location speed, higher precision and lower hardware cost. Finally, the field operation test further validated that such autonomous location control method was of strong engineering practicability.

The proposed autonomous location control method is adaptable to a flexible environment and to the structural parameters of different types of drainage board. Simulation results confirm the effectiveness of the proposed method, which, in comparison with other approaches to location control, can achieve faster location, higher precision and lower hardware cost. Finally, a field test further confirms the engineering practicability of the proposed autonomous location control method.

The proposed method can achieve faster location speed, higher precision which meet the requirement of real-time control relative to the standard BP algorithm. Moreover, it is of strong adaptability to flexible environment and structural parameters for different drainage board. Field operation experiment further validated the engineering practicability of the method.

This paper aims to conduct a detailed analysis of the industrial practices currently being used in the geothermal energy industry and to determine whether they are contributing to any limitations. A HAZOP-based upgradation model for improvement in existing industrial practices is proposed to ensure the removal of inefficient conventional practices. The HAZOP-based upgradation model examines the setbacks, identifies its causes and consequences and suggests improvement methods comprising of modern-day technology.

This paper proposed a HAZOP-based upgradation model for improvement in existing industrial practices. The proposed HAZOP model identifies the drawbacks brought on by conventional practices and suggests improvements.

The study reviewed the challenges geothermal power plants currently face due to conventional practices and suggested a total of 22 upgradation recommendations. From those, a total of 11 upgradation modules comprising modern digital technology and Industry 4.0 elements were proposed to improve the existing practices in the geothermal energy industry. Autonomous robots, augmented reality, machine learning and Internet of Things were identified as useful methods for the upgradation of the existing geothermal energy system.

If proposed recommendations are incorporated, the efficiency of geothermal energy generation will increase as cumulating setbacks will no longer degrade the work output.

The proposed recommendation by the study will make way for Industry 4.0 integration with the geothermal energy sector.

The paper uses a proposed HAZOP-based upgradation model to review issues in existing industrial practices of the geothermal energy sector and recommends solutions to overcome operability issues using Industry 4.0 technologies.

Purpose – The purpose of this chapter is to analyse the evolution in the local, global and multinational network embeddedness of foreign subsidiaries in China

Methodology – The study focuses on Sino-Belgian subsidiaries in China. Factor analysis was used to determine the local responsiveness, global integration and multinational network embeddedness of firms. Next cluster analysis was carried out to classify groups of subsidiaries, while ANOVA analysis assessed their different characteristics.

Findings – Although most firms remain the same type of subsidiary throughout the period of 1995–2005, the most prevalent trajectory of strategic evolution by multinational subsidiaries in China is by increasing the integration in the multinational network before gaining more local embeddedness towards a more active role within the multinational network.

Research implications – Changes in the strategic setting and operations of MNEs occur over time because of the dynamic patterns and changing interactions of firm- and country-related factors and policies, especially when the host economy is involved in a rapid transformation process, such as China. Further research could focus on the determinants of strategic evolution.

Originality – This is one of the first chapters to analyse the changing roles of subsidiaries, in particular in an emerging economy.

The purpose of the study was to examine travelers’ attitudinal and behavioral loyalty to the product type of peer-to-peer (P2P) accommodations (as opposed to a brand).

P2P accommodations’ hosts provided contact information for their guests from the prior two years who were contacted to participate in the study. Respondents answered questions about their travel party, trip purpose, factors leading to their P2P accommodation stay and attitudinal and behavioral loyalty around P2P lodging.

Autonomous motivators (dislike of big hotel chains and experience authenticity) and controlled motivators (location and cooking facilities) were positively related to attitudinal loyalty to P2P accommodations. Price predicted behavioral loyalty in the form of repeat purchase behavior and attitudinal loyalty did not.

Limitations of this study include the representativeness and size of the sample, the generalizability of the results, cross-sectional nature of the data and respondents’ recall ability. Despite a favorable attitude toward P2P accommodations, only price accounted for travelers’ repeated choice of P2P accommodations over hotels.

While attitudinal loyalty was explained by the dislike of big hotel chains and experience authenticity in P2P accommodations, it did not translate into repeated purchase behavior. Behavioral loyalty to P2P seems all about price, which begs the question of whether price is the most meaningful competitive lever in the battle between conventional hotels and P2P.

Hotel brand loyalty refers to consumer choice of brand within the conventional hotel product type. This study presents the first effort to understand consumer loyalty to a lodging product type, specifically P2P accommodations, and not a particular brand.

ROBOVOLC is a new robotic system that has been designed to help scientists in the exploration of volcanoes. It is composed of three subsystems: a rover platform with six articulated and independently actuated wheels; a manipulator arm to collect rock samples, drop and pick up sensors and sample gas; and a pan‐tilt turret with a high resolution camera, video‐camera, infrared camera and a doppler radar for gas speed measurement. This paper contains a short description of the system, following an introduction to the problem and review of the state‐of‐the‐art. Finally, results from the first test campaign on Mount Etna during September 2002 are briefly described.

In the long-term network operation, the power distribution network will be subjected to the effects of ultra-high voltage, strong electromagnetic interference and harsh natural environment on the power system, which will lead to the occurrence of different faults in the distribution network and directly affect the normal operation of the power grid.

The purpose of this study is to solve the problems of labor intensity, high risk and low efficiency of distribution network manual maintenance operation, this paper proposed a new configuration of the live working robot for distribution network maintenance, the robot is equipped with dual working arms through the mobile platform, which can realize the coordination movement, the autonomous reorganization and replacement of the end tools, respectively, so as the robot power distribution maintenance function such as stripping, trimming, wiring and the operation control problem of the distribution network-robot with small arms and in small operation space can be realized.

To effective elimination or reduce the adverse effects of the internal forces in the closed chain between the working object and manipulator under the typical task of the 10 kV distribution network, this paper has established the robot coordinated control dynamics model in the closed-chain between the dual-working object and proposed the dynamic distribution method of closed-chain internal force and the effectiveness has been proved by simulation experiments and 10 kV field operation.

The force-position hybrid control can realize the mutual compensation of force and position so as to effectively reduce the internal force in the closed chain. Finally, the engineering practicality of the method is verified by field operation experiment, the effective implementation of this control method greatly improves the robot working efficiency and the operation reliability, the promotion and application of the control method have great theoretical and practical value and maintenance management system, so as to achieve automation of electric.

The purpose of this study is to solve the key technical problems of the practical application of electric robots. The UHV multi-split transmission line power cable operation robot is an important equipment to ensure the reliable operation of high voltage lines and is a useful exploration to realize high-quality power transmission. As the robot system platform equipment mature and operation environment gradually become more complex, the double arm coordination motion control in extreme environment becomes one of the main bottleneck for its practical in power system.

This paper summarizes the key technologies related to power cable robots, and aims at key technical indicators such as operation reliability, operation efficiency and operation quality in the robot’s practical process. The dynamic evolution mechanism of the robot’s mechanical configuration, the multi-physics information fusion algorithm in extreme environments, the robot’s autonomous positioning and its error compensation control, the robot’s robust motion control in extreme environments and the dual-arm force-position hybrid coordination control and the dynamic distribution and elimination mechanism of internal forces in the closed chain between robots and operating objects, all the research methods and solutions of the key technologies are proposed, respectively.

Finally, a new control architecture for power cable robots in the background of the Ubiquitous Power Internet of Things is proposed so as to manage the operation and maintenance of electric power systems. The above key technologies are a new exploration of the operation and maintenance management of EHV (Extra High Voltage) multi-split transmission lines which have laid a solid theoretical foundation for the power cable robot.

High voltage transmission line is the main channel of power transmission. It is an important means to improve the integration of operation and maintenance management of power system to use robot instead of manual inspection and maintenance of power line, in the promotion and application of electric robot. The authors pay attention to the practicability, and the breakthrough of key technologies of robot is the premise of the practicability of robot. In this paper, the robot operation and control in multi-task and complex scenes are studied. The research and implementation of the main key technologies, such as the dynamic evolution mechanism of robot configuration, the coupling and fusion law of multi physical fields in the extreme electric power environment, the autonomous positioning control of manipulator, the robust control of robot in the super electromagnetic field environment and the cooperative operation control of multi manipulator, are discussed.

The purpose of this paper is to verify the correctness and feasibility of simultaneous localization and mapping (SLAM) algorithm based on red-green-blue depth (RGB-D) camera in high precision navigation and localization of celestial exploration rover.

First, a positioning algorithm based on depth camera is proposed. Second, the realization method is described from the five aspects of feature detection method, feature point matching, point cloud mapping, motion estimation and high precision optimization. Feature detection: taking the precision, real-time and motion basics as the comprehensive consideration, the ORB (oriented FAST and rotated BRIEF) features extraction method is adopted; feature point matching: solves the similarity measure of the feature descriptor vector and how to remove the mismatch point; point cloud mapping: the two-dimensional information on RGB and the depth information on D corresponding; motion estimation: the iterative closest point algorithm is used to solve point set registration; and high precision optimization: optimized by using the graph optimization method.

The proposed high-precision SLAM algorithm is very effective for solving high precision navigation and positioning of celestial exploration rover.

In this paper, the simulation validation is based on an open source data set for testing; the physical verification is based on the existing unmanned vehicle platform to simulate the celestial exploration rover.

This paper presents a RGB-D camera-based navigation algorithm, which can be obtained by simulation experiment and physical verification. The real-time and accuracy of the algorithm are well behaved and have strong applicability, which can support the tests and experiments on hardware platform and have a better environmental adaptability.

The proposed SLAM algorithm can deal with the high precision navigation and positioning of celestial exploration rover effectively. Taking into account the current wide application prospect of computer vision, the method in this paper can provide a study foundation for the deep space probe.