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Since the market penetrations of service robots are only successful to a limited types of services, the purpose of the paper is to look into the reasons why the market penetrations are lagged from both technical and nontechnical perspectives. Automatic robotic recharging services, especially robotic refueling systems, are used as the case study for the investigation.

This paper surveyed the relevant technologies and products and conducted the feasibility study and risk management for new development of automated robotic refueling systems. This paper developed a cost model for the evaluation of robotic refueling systems.

There are no major technical barriers that exist for the development of robotic refueling systems, but two main risks of developing new robotic refueling systems are interference of existing patents and the extreme effort to further reduce the development cost of automated refueling systems. The recommendations have been made to new developers of service robots.

The suggestions are made for further development on service robots, in general; however, this paper does not cover the physical development of service robots.

This study was actually conducted for a client company who has a strong interest in developing new products for automatic robotic refueling systems. The reported work has great significance for new comers in this area to understand the state of the art, technological challenges and some potential risks in the field.

To the best of authors’ knowledge, it will be the first academic paper to summarize the research and development effort on automatic recharging business. The targeted field is very typical in promoting robots in services. Even robotic refueling was proposed at very early stage of robotic application, the market penetration of refueling robots the market penetration is very limited, not because the technology readiness but some other factors. This work has its significance to identify technical and nontechnical challenges to promote robots in services.

The purpose of this paper is to develop a monocular visual measurement system for autonomous aerial refueling (AAR) for unmanned aerial vehicle, which can process images from an infrared camera to estimate the pose of the drogue in the tanker with high accuracy and real-time performance.

Methods and techniques for marker detection, feature matching and pose estimation have been designed and implemented in the visual measurement system.

The simple blob detection (SBD) method is adopted, which outperforms the Laplacian of Gaussian method. And a novel noise-elimination algorithm is proposed for excluding the noise points. Besides, a novel feature matching algorithm based on perspective transformation is proposed. Comparative experimental results indicated the rapidity and effectiveness of the proposed methods.

The visual measurement system developed in this paper can be applied to estimate the pose of the drogue with a fast speed and high accuracy and it is a feasible measurement strategy which will considerably increase the autonomy and reliability for AAR.

The SBD method is used to detect the features and a novel noise-elimination algorithm is proposed. Besides, a novel feature matching algorithm based on perspective transformation is proposed which is robust and accurate.

This chapter outlines the potential market of methane (especially LNG) as vehicle fuel in Europe and China.

A comprehensive report on the existing framework in terms of market capacity, regulations, and incentives is presented. Moreover, the feasibility of using biogas as environmental friendly source gas is considered.

The transport sector represents a major element in the global balance of greenhouse gas (GHG) emissions. Natural gas is considered the alternative fuel that, in the short-medium term, can best substitute conventional fuels in order to reduce their environmental impact, because it is readily available at a competitive price, using technologies that are already in widespread use. It can be used as compressed gas (CNG) or in the liquid phase (LNG). The former is more suitable for light vehicles, while the latter for heavy-duty vehicles. Some barriers need to be overcome for the diffusion of this alternative fuel, especially concerning the supply problem. The incentive policy has been shown to cover a major influence in the feasibility evaluation.

This work shows the state of the art of natural gas as fuel, especially from biogas source, in Europe and China and assesses the incentive scheme necessary to make liquefied biomethane feasible on the basis of the existing scenario in Italy.

Motivated by a problem in the context of DiDi Travel, the biggest taxi hailing platform in China, the purpose of this paper is to propose a novel facility location problem, specifically, the single source capacitated facility location problem with regional demand and time constraints, to help improve overall transportation efficiency and cost.

This study develops a mathematical programming model, considering regional demand and time constraints. A novel two-stage neighborhood search heuristic algorithm is proposed and applied to solve instances based on data sets published by DiDi Travel.

The results of this study show that the model is adequate since new characteristics of demand can be deduced from large vehicle trajectory data sets. The proposed algorithm is effective and efficient on small and medium as well as large instances. The research also solves and presents a real instance in the urban area of Chengdu, China, with up to 30 facilities and demand deduced from 16m taxi trajectory data records covering around 16,000 drivers.

This study examines an offline and single-period case of the problem. It does not consider multi-period or online cases with uncertainties, where decision makers need to dynamically remove out-of-service stations and add other stations to the selected group.

Prior studies have been quite limited. They have not yet considered demand in the form of vehicle trajectory data in facility location problems. This study takes into account new characteristics of demand, regional and time constrained, and proposes a new variant and its solution approach.

The purpose of this paper is to propose a new algorithm for linear-quadratic regulator (LQR) controller of a quadrotor with fast and stable performance, which is based on pigeon-inspired optimization (PIO).

The controller is based on LQR. The determinate parameters are optimized by PIO, which is a newly proposed swarm intelligent algorithm inspired by the characteristics of homing pigeons.

The PIO-optimized LQR controller can obtain the optimized parameters and achieve stabilization in about 3 s.

The PIO-optimized LQR controller can be easily applied to the flight formation, autonomous aerial refueling (AAR) and detection of unmanned aerial vehicles, especially applied to (AAR) in this paper.

This research applies PIO to optimize the tuning parameters of LQR, which can considerably improve the fast and stabilizing performance of attitude control. The simulation results show the effectiveness of the proposed algorithm.

Technology for training military teams has evolved through a convergence of advances in simulation technology for individual and collective training, methods for analyzing teamwork and designing training solutions, and intelligent tutoring technologies that adapt training to the student, to accelerate learning. A number of factors have slowed this evolution toward intelligent team tutoring systems (ITTS), including the challenges of processing communications data, which are the currency of teamwork, and the paucity of automated and generalizable measures of team work. Several systems fulfill a subset of the features required of an ITTS, namely the use of team training objectives, teamwork models, measures of teamwork, diagnostic capability, instructional strategies, and adaptation of training to team needs. We describe these systems: the Advanced Embedded Training System (AETS), Synthetic Cognition for Operational Team Training (SCOTT), the AWO Trainer, the Benchmarked Experiential System for Training (BEST), and the Cross-Platform Mission Visualization Tool. We close this chapter with recommendations for future research.

UAVs have been used by military forces since at least the War of Attrition – fought between Egypt and Israel between 1967 and 1970 – when the Israeli Army modified radio-controlled model aircraft to fly over the Suez Canal and take aerial photographs behind Egyptian lines (Bolia, 2004). Although the Israelis ill advisedly abandoned the concept before the Yom Kippur War, it was taken up by several nations in the ensuing decades, and today UAVs are regarded as a routine component of surveillance operations, having played a significant role in both Afghanistan and Iraq.

An automated machining cell installed at Flight Refuelling in the UK was described at the recent FMS‐4 conference in Stockholm