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The purpose of this paper is to propose a generic platform for a robotic mobile system, seeking to obtain a support tool for under-graduation and graduation activities. Another objective was to gather knowledge in the mobile robotic area in order to provide practical solutions for industrial problems.

The proposed new integrated platform would serve as didactic material for many disciplines, shown to be an ideal platform to teach DC motor drives, stepper motor and motion-control systems. To reach this objective, the ability of the robot to plan its motion autonomously is of vital importance. The control of a mobile robot in dynamic and unstructured environments typically requires efficient processing of data/information to ensure precise navigation and many other applications. Path planning is also one common method of auto-navigation. After the computation of the shortest path, mobile robot can navigate safely and without occlusion.

The developed platform is an integrated system for intelligent software middleware to coordinate many activities in the field of electric drives, robotics, autonomous systems and artificial intelligence.

As a result of the study, this paper contributed to research in the industrial development, principally in the fields of industrial robotics and also in different application purposes such as entertainment, personal use, welfare, education, rehabilitation, etc.

The purpose of this paper is to introduce a new danger‐aware Operational Flight Program (OFP) for the unmanned helicopter's auto‐navigation based on the well‐known time‐triggered message‐triggered object (TMO) model.

In this design with the TMO, the danger‐awareness means two things. First, an unmanned helicopter maneuvers on safe altitudes to avoid buildings or mountains when navigating to the target position. It is assumed that minimum safe altitudes are given on evenly spaced grids and on the center points of every four adjacent grids. A three‐dimensional (3D) path‐finding algorithm using this safe‐altitude information is proposed. Second, a helicopter automatically avoids a zone with very high temperature caused by a fire.

Since the auto‐flight control system requires componentized real‐time processing of sensors and controllers, the TMO model that has periodic and sporadic threads as members, has been used in designing the OFP. It has been found that using the TMO scheme is a way to construct a very flexible, well‐componentized and timeliness‐guaranteed OFP.

As the RTOS, RT‐eCos has been used. It was developed a few years ago based on the eCos3.0 to support the real‐time thread model of the TMO scheme. To verify this navigation system, a hardware‐in‐the‐loop simulation (HILS) system also has been developed.

Designing an OFP by using the real‐time object model TMO and the proposed 3D safe path finding algorithm is a whole new effective deadline‐based approach. And the developed OFP can be used intensively in the phase of disaster response and recovery.

Examines a prototype robot which is being developed to carry out non‐destructive inspection maintenance and repair [IMR] of buildings and structures. Describes some of the areas where IMR is crucial i.e. bridges, tall buildings and petro‐chemical storage tanks and the variety of inspection tasks a robot would be required to carry out. Looks at the essential technologies to be considered for a successful inspection robot and outlines the areas of access and mobility, robot construction, control strategy and the external sensing systems it would need. Concludes that this prototype is capable of delivering single NDT packages and that in the future it is intended that the robot will be able to exchange its own NDT packages. Expresses some reservation about whether a free climbing version would be viable.

The purpose of this paper is to design and implement a landmine detection robot (Venus) equipped with three electromagnetic sensors and controlled by ordered weighted averaging (OWA) sensor fusion approach. Higher numbers of detected mines in a fixed time interval and lower total power consumption are the achieved goals of this research.

OWA sensor fusion is exploited for data combination in this paper. Unlike most other landmine detection robots, Venus has three electromagnetic sensors, the positions of which can be adjusted according to the environmental conditions. Also, a novel approach for OWA weight dedication using Gaussian distribution function is applied and the whole idea is evaluated practically in several randomly mined fields. Finally, for better evaluation, performance of Venus is compared with the other two landmine detection robots.

The simulation and experimental results proved that in a predetermined interval of time, not only total energy consumption is reduced, but also by expanding the surface and the depth of influence of electromagnetic waves, the number of detected mines is considerably raised.

In contrast to the regular demining process, which is relatively expensive and complicated, the landmine detection method proposed in this research is surprisingly simple, cost effective, and efficient. Therefore, it may be attractive for every company or organization in this field of research.

The paper describes research which implements and evaluates a novel control approach based on OWA sensor fusion method, a new way of using Gaussian distribution function for determining OWA weights, and also an adaptive physical configuration for sensors based on environmental conditions.

Global navigation satellite systems (GNSS) were designed to determine the exact location of objects on land, water and air for military purposes. With the opening of the satellite signal for civilian use, the technology created business opportunities for various applications. Today, satellite positioning technology is used by transporters, carriers, motorists, surveyors, builders, foresters, etc. through a wide array of devices like mobile phones or multimedia devices with built-in receiver modules.

This paper provides the results of a recently held foresight exercise on the future development of Russia’s GLONASS system.

The foresight exercise suggested a number niche markets where the GLONASS technology could be of great use, like monitoring of buildings and construction sides or the monitoring of shipments. In addition, in the case of Russia, large-scale government-driven investment programs will be key drivers for GLONASS’ growth perspectives.

The paper provides a comprehensive picture of the development of GNSS for civilian use until 2020.