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The purpose of this research is to provide the necessarily and resourceful information regarding range sensors to select the best fit sensor for robust autonomous navigation. Autonomous navigation is an emerging segment in the field of mobile robot in which the mobile robot navigates in the environment with high level of autonomy by lacking human interactions. Sensor-based perception is a prevailing aspect in the autonomous navigation of mobile robot along with localization and path planning. Various range sensors are used to get the efficient perception of the environment, but selecting the best-fit sensor to solve the navigation problem is still a vital assignment.

Autonomous navigation relies on the sensory information of various sensors, and each sensor relies on various operational parameters/characteristic for the reliable functioning. A simple strategy shown in this proposed study to select the best-fit sensor based on various parameters such as environment, 2 D/3D navigation, accuracy, speed, environmental conditions, etc. for the reliable autonomous navigation of a mobile robot.

This paper provides a comparative analysis for the diverse range sensors used in mobile robotics with respect to various aspects such as accuracy, computational load, 2D/3D navigation, environmental conditions, etc. to opt the best-fit sensors for achieving robust navigation of autonomous mobile robot.

This paper provides a straightforward platform for the researchers to select the best range sensor for the diverse robotics application.

The purpose of this paper is to discuss the autonomous navigation and guidance scheme for future precise and safe planetary landing.

Autonomous navigation and guidance schemes are proposed based on inertial measurement unit (IMU) and optical navigation sensors for precise and safe landing of spacecrafts on the moon and planetary bodies. First, vision‐aided inertial navigation scheme is suggested to achieve precise relative navigation; second, two autonomous obstacle detection algorithms, based on grey image from optical navigation camera and digital elevation map form light detection and ranging sensor, respectively, are proposed; and third, flowchart of automatic obstacle avoidance maneuver is also given out.

This paper finds that the performance of the proposed scheme precedes the traditional planetary landing navigation and guidance mode based on IMU and deep space network.

The presented schemes need to be further validated by the mathematical simulations and hardware‐in‐loop simulations, and then they can be used in the real flight missions.

The presented schemes are applicable to both future planetary pin‐point landing missions and sample return missions with little modification.

This paper presents the new autonomous navigation and guidance scheme in order to achieve the precise and safe planetary landing.

The authors present a low-cost unmanned aerial vehicle (UAV) for autonomous flight and navigation in GPS-denied environments using an off-the-shelf smartphone as its core on-board processing unit. Thereby, the approach is independent from additional ground hardware and the UAV core unit can be easily replaced with more powerful hardware that simplifies setup updates as well as maintenance. The paper aims to discuss these issues.

The UAV is able to map, locate and navigate in an unknown indoor environment fusing vision-based tracking with inertial and attitude measurements. The authors choose an algorithmic approach for mapping and localization that does not require GPS coverage of the target area; therefore autonomous indoor navigation is made possible.

The authors demonstrate the UAVs capabilities of mapping, localization and navigation in an unknown 2D marker environment. The promising results enable future research on 3D self-localization and dense mapping using mobile hardware as the only on-board processing unit.

The proposed autonomous flight processing pipeline robustly tracks and maps planar markers that need to be distributed throughout the tracking volume.

Due to the cost-effective platform and the flexibility of the software architecture, the approach can play an important role in areas with poor infrastructure (e.g. developing countries) to autonomously perform tasks for search and rescue, inspection and measurements.

The authors provide a low-cost off-the-shelf flight platform that only requires a commercially available mobile device as core processing unit for autonomous flight in GPS-denied areas.

This work analyses autonomous ships' specific needs of external and environmental information in restricted pilotage waters. Harbour pilots use conventional well-tested techniques when piloting the manned vessel. In this work, the authors propose technological solutions to be installed or adapted in ports to feed the autonomous ships' systems with the information considered relevant by pilots.

To investigate what pilots consider relevant, the authors submitted a questionnaire to the pilotage of Paranaguá Port. Then the authors presented a case study including the critical areas for the navigation of ships.

These technological solutions aim to allow vessels reaching critical areas in a position, a time, a speed and a course that compensates the external forces and/or avoid high-risk situations. The authors have proposed technological solutions considering those already available in the ports, particularly in Paranaguá and Antonina in Brazil.

There is little published data on navigation of ships in pilotage waters. So far, there has been little discussion on autonomous ships in restricted waters.

This paper aims to propose a series of approaches to solve the problem of the mobile robot motion control and autonomous navigation in large-scale outdoor GPS-denied environments.

Based on the model of mobile robot with two driving wheels, a controller is designed and tested in obstacle-cluttered scenes in this paper. By using the priori “topology-geometry” map constructed based on the odometer data and the online matching algorithm of 3D-laser scanning points, a novel approach of outdoor localization with 3D-laser scanner is proposed to solve the problem of poor localization accuracy in GPS-denied environments. A path planning strategy based on geometric feature analysis and priority evaluation algorithm is also adopted to ensure the safety and reliability of mobile robot’s autonomous navigation and control.

A series of experiments are conducted with a self-designed mobile robot platform in large-scale outdoor environments, and the experimental results show the validity and effectiveness of the proposed approach.

The problem of motion control for a differential drive mobile robot is investigated in this paper first. At the same time, a novel approach of outdoor localization with 3D-laser scanner is proposed to solve the problem of poor localization accuracy in GPS-denied environments. A path planning strategy based on geometric feature analysis and priority evaluation algorithm is also adopted to ensure the safety and reliability of mobile robot’s autonomous navigation and control.

This study aims to find a feasible precise navigation model for the planed Lunar rover. Autonomous navigation is one of the most important missions in the Chinese Lunar exploration project. Machine vision is expected to be a promising option for this mission because of the dramatic development of an image processing technique. However, existing attempts are often subject to low accuracy and errors accumulation.

In this paper, a novel autonomous navigation model was developed, based on the rigid geometric and photogrammetric theory, including stereo perception, relative positioning and absolute adjustment. The first step was planned to detect accurate three-dimensional (3D) surroundings around the rover by matching stereo-paired images; the second was used to decide the local location and orientation changes of the rover by matching adjacent images; and the third was adopted to find the rover’s location in the whole scene by matching ground image with satellite image. Among them, the SURF algorithm that had been commonly believed as the best algorithm for matching images was adopted to find matched images.

Experiments indicated that the accurate 3D scene, relative positioning and absolute adjustment were easily generated and illustrated with the matching results. More importantly, the proposed algorithm is able to match images with great differences in illumination, scale and observation angle. All experiments and findings in this study proved that the proposed method could be an alternative navigation model for the planed Lunar rover.

With the matching results, an accurate 3D scene, relative positioning and absolute adjustment of rover can be easily generated. The whole test proves that the proposed method could be a feasible navigation model for the planed Lunar rover.

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 present a variable structure multiple model adaptive estimator (VSMMAE) for liaison navigation system. Liaison navigation is an autonomous navigation method where inter-satellite range measurements are used to estimate the orbits of all participating spacecrafts simultaneously.

To overcome the problem caused by an inaccurate initial state, a navigation algorithm is designed based on the multiple model adaptive estimation technique. The multiple models are constructed by different initial error covariance matrices. To reduce the computational cost, the likely-model set (LMS) algorithm is adopted to eliminate the unlikely models.

It is specified that the performance of the liaison navigation based on the extended Kalman filter (EKF) is sensitive to the initial error. Simulation results show that the VSMMAE outperforms the EKF in the presence of a large initial error.

The presented algorithm is applicable to spacecraft autonomous navigation.

A novel navigation algorithm based on the VSMMAE is developed. It is an effective method for the liaison navigation system.

The purpose of this paper is to propose a seamless autonomous navigation method based on the motion constraint of the mobile robot, which is able to meet the practical need of maintaining the navigation accuracy during global positioning system (GPS) outages.

The seamless method uses the motion constraint of the mobile robot to establish the filter model of the system, in which the virtual observation about the speed is used to overcome the shortage of the navigation accuracy during GPS outages. The corresponding motion constraint model of the mobile robot is established. The proposed seamless navigation scheme includes two parts: the micro inertial navigation system (MINS)/GPS-integrated filter model and the motion constraint filter model. When the satellite signals are good, the system works on the MINS/GPS-integrated mode. If some obstacles block the GPS signals, the motion constraint measurement equation will be effective so as to improve the navigation accuracy of the mobile robot.

Three different vehicle tests of the mobile robot show that the seamless navigation method can overcome the shortage of the navigation accuracy during GPS outages, so as to improve the navigation performance in practical applications.

A seamless navigation system based on the motion constraint of the mobile robot is proposed to overcome the shortage of the navigation accuracy during GPS outages, thus improving the adaptability of the robot navigation.

Recently there has been a strong trend towards automation in the mine industry. This paper seeks to describe and analyse an algorithm that can be used as a part of an infrastructure‐free reactive navigation system for autonomous vehicles in underground mines.

The idea presented here to enable infrastructure‐free autonomous navigation is to combine reactive behaviours for tunnel following, with topological localization. To assess the reliability and precision of the corridor detection algorithm real data recorded in both indoor and mine environments have been used.

In the research it was found that the algorithm is able to reliably detect corridors even in difficult environments such as office corridors where a large part of the walls are made of glass or in mine tunnels with a high intensity of intersections. It was also concluded that the algorithm provides good enough precision and robustness to noise in the data to enable reactive tunnel following.

This paper presents an algorithm for corridor detection, intended to be used in combination with reactive behaviours for tunnel following in underground mines. To enable fully autonomous navigation, functionality to detect and turn at intersections also needs to be developed.

This research shows that corridor detection can be used for reactive tunnel following in certain underground mine types, and that the concept of using reactive tunnel following in combination with topological localization is worthy of continued development.

This paper has presented a new algorithm for corridor detection based on the Hough transform. The algorithm is robust to noise in the data and can reliably detect corridors even where the surfaces of the walls are uneven and slightly curved.