298 research outputs found
Engineering data compendium. Human perception and performance. User's guide
The concept underlying the Engineering Data Compendium was the product of a research and development program (Integrated Perceptual Information for Designers project) aimed at facilitating the application of basic research findings in human performance to the design and military crew systems. The principal objective was to develop a workable strategy for: (1) identifying and distilling information of potential value to system design from the existing research literature, and (2) presenting this technical information in a way that would aid its accessibility, interpretability, and applicability by systems designers. The present four volumes of the Engineering Data Compendium represent the first implementation of this strategy. This is the first volume, the User's Guide, containing a description of the program and instructions for its use
Survey of computer vision algorithms and applications for unmanned aerial vehicles
This paper presents a complete review of computer vision algorithms and vision-based intelligent applications, that are developed in the field of the Unmanned Aerial Vehicles (UAVs) in the latest decade. During this time, the evolution of relevant technologies for UAVs; such as component miniaturization, the increase of computational capabilities, and the evolution of computer vision techniques have allowed an important advance in the development of UAVs technologies and applications. Particularly, computer vision technologies integrated in UAVs allow to develop cutting-edge technologies to cope with aerial perception difficulties; such as visual navigation algorithms, obstacle detection and avoidance and aerial decision-making. All these expert technologies have developed a wide spectrum of application for UAVs, beyond the classic military and defense purposes. Unmanned Aerial Vehicles and Computer Vision are common topics in expert systems, so thanks to the recent advances in perception technologies, modern intelligent applications are developed to enhance autonomous UAV positioning, or automatic algorithms to avoid aerial collisions, among others. Then, the presented survey is based on artificial perception applications that represent important advances in the latest years in the expert system field related to the Unmanned Aerial Vehicles. In this paper, the most significant advances in this field are presented, able to solve fundamental technical limitations; such as visual odometry, obstacle detection, mapping and localization, et cetera. Besides, they have been analyzed based on their capabilities and potential utility. Moreover, the applications and UAVs are divided and categorized according to different criteria.This research is supported by the Spanish Government through the CICYT projects (TRA2015-63708-R and TRA2013-48314-C3-1-R)
PLD-SLAM: A Real-Time Visual SLAM Using Points and Line Segments in Dynamic Scenes
In this paper, we consider the problems in the practical application of
visual simultaneous localization and mapping (SLAM). With the popularization
and application of the technology in wide scope, the practicability of SLAM
system has become a new hot topic after the accuracy and robustness, e.g., how
to keep the stability of the system and achieve accurate pose estimation in the
low-texture and dynamic environment, and how to improve the universality and
real-time performance of the system in the real scenes, etc. This paper
proposes a real-time stereo indirect visual SLAM system, PLD-SLAM, which
combines point and line features, and avoid the impact of dynamic objects in
highly dynamic environments. We also present a novel global gray similarity
(GGS) algorithm to achieve reasonable keyframe selection and efficient loop
closure detection (LCD). Benefiting from the GGS, PLD-SLAM can realize
real-time accurate pose estimation in most real scenes without pre-training and
loading a huge feature dictionary model. To verify the performance of the
proposed system, we compare it with existing state-of-the-art (SOTA) methods on
the public datasets KITTI, EuRoC MAV, and the indoor stereo datasets provided
by us, etc. The experiments show that the PLD-SLAM has better real-time
performance while ensuring stability and accuracy in most scenarios. In
addition, through the analysis of the experimental results of the GGS, we can
find it has excellent performance in the keyframe selection and LCD
The simultaneous localization and mapping (SLAM):An overview
Positioning is a need for many applications related to mapping and navigation either in civilian or military domains. The significant developments in satellite-based techniques, sensors, telecommunications, computer hardware and software, image processing, etc. positively influenced to solve the positioning problem efficiently and instantaneously. Accordingly, the mentioned development empowered the applications and advancement of autonomous navigation. One of the most interesting developed positioning techniques is what is called in robotics as the Simultaneous Localization and Mapping SLAM. The SLAM problem solution has witnessed a quick improvement in the last decades either using active sensors like the RAdio Detection And Ranging (Radar) and Light Detection and Ranging (LiDAR) or passive sensors like cameras. Definitely, positioning and mapping is one of the main tasks for Geomatics engineers, and therefore it's of high importance for them to understand the SLAM topic which is not easy because of the huge documentation and algorithms available and the various SLAM solutions in terms of the mathematical models, complexity, the sensors used, and the type of applications. In this paper, a clear and simplified explanation is introduced about SLAM from a Geomatical viewpoint avoiding going into the complicated algorithmic details behind the presented techniques. In this way, a general overview of SLAM is presented showing the relationship between its different components and stages like the core part of the front-end and back-end and their relation to the SLAM paradigm. Furthermore, we explain the major mathematical techniques of filtering and pose graph optimization either using visual or LiDAR SLAM and introduce a summary of the deep learning efficient contribution to the SLAM problem. Finally, we address examples of some existing practical applications of SLAM in our reality
OBJECT PERCEPTION IN UNDERWATER ENVIRONMENTS: A SURVEY ON SENSORS AND SENSING METHODOLOGIES
Underwater robots play a critical role in the marine industry. Object perception is the foundation for the automatic
operations of submerged vehicles in dynamic aquatic environments. However, underwater perception
encounters multiple environmental challenges, including rapid light attenuation, light refraction, or backscattering
effect. These problems reduce the sensing devices’ signal-to-noise ratio (SNR), making underwater
perception a complicated research topic. This paper describes the state-of-the-art sensing technologies and
object perception techniques for underwater robots in different environmental conditions. Due to the current
sensing modalities’ various constraints and characteristics, we divide the perception ranges into close-range,
medium-range, and long-range. We survey and describe recent advances for each perception range and suggest
some potential future research directions worthy of investigating in this field
Visual-based SLAM configurations for cooperative multi-UAV systems with a lead agent: an observability-based approach
In this work, the problem of the cooperative visual-based SLAM for the class of multi-UA systems that integrates a lead agent has been addressed. In these kinds of systems, a team of aerial robots flying in formation must follow a dynamic lead agent, which can be another aerial robot, vehicle or even a human. A fundamental problem that must be addressed for these kinds of systems
has to do with the estimation of the states of the aerial robots as well as the state of the lead agent.
In this work, the use of a cooperative visual-based SLAM approach is studied in order to solve the above problem. In this case, three different system configurations are proposed and investigated by means of an intensive nonlinear observability analysis. In addition, a high-level control scheme is proposed that allows to control the formation of the UAVs with respect to the lead agent. In this work, several theoretical results are obtained, together with an extensive set of computer simulations which are presented in order to numerically validate the proposal and to show that it can perform well under different circumstances (e.g., GPS-challenging environments). That is, the proposed method is able to operate robustly under many conditions providing a good position estimation of the aerial vehicles and the lead agent as well.Peer ReviewedPostprint (published version
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