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Visual Odometry (VO) is the process of calculating the motion of an agent (such as, robot and vehicle), using images captured by a single or multiple cameras embedded to it. VO is an important process to supplement autonomous navigation systems, since VO can provide accurate trajectory estimates. This process can be used to perform a 3D mapping, in order to provide more information during a vehicle...
The growth of 3D visualization devices, such as holograms and virtual reality, is followed by the increase of demand for 3D models. One cheap and straightforward way of creating them is by photogrammetry. However, taking the necessary photographs is tedious and imprecise, because many different shooting angles and heights are required. Also, there may be need of doing models of objects placed on hazardous...
3D point cloud classification is an important task in applications for many areas such as robotics, urban planning and augmented reality. 3D sensors measure a high amount of points in the 3D scene objects' surface at a high collect rate, so robust techniques are needed to process all input data and also deal with some imprecision. A common solution for these tasks is the use of robust features extraction...
The use of Multi-Robot Systems presents several advantages like increased robustness and, in most cases, time reduction to accomplish a task. In this context, Robotic Swarms is generally related to very large groups of robots. The congestion problem within the mobile robotics field is a well-known field of research. The problem occurs when a large number of autonomous robots tries to reach a common...
Obstacle detection and tracking is a fundamental task for several Advanced Driver Assistance Systems (ADAS) and self-driving cars. Several approaches have been presented in the literature in the last years and many of them are based on visual sensors. In this paper we propose an approach that uses only stereo cameras to detect and track obstacles and compute visual odometry to get the vehicle's ego-velocity...
This paper presents a system for classifying images based on Deep Learning and applied in the recognition of traffic signals aiming to increase road safety increased road safety using autonomous and semi-autonomous intelligent robotic vehicles. This Advanced Driver Assistance System (ADAS) is a system created to automate vehicles, but also to help the human drivers to increase safety and the respect...
A big challenge in the precision agriculture is the detection of fruits in coffee crops on agricultural environments. This paper presents a comparison of four features set to detect the red fruits (mature) in Coffee plants. An Unmanned Aerial Vehicle (UAV) is used to obtain high-resolution RGB images of a coffee hall. The proposed methodology enables the extraction of visual features from image regions...
Weather stations are a valuable tool to many different areas, like agriculture, aviation, construction, sports and recreation, specially because they collect weather data, which can be stored and processed to gather specific information to correlate events to the weather action. This work shows a development model of a low cost weather station, using only free hardware and software, connected to the...
Robotics has been used to draw the attention of young students to computing and engineering. Unfortunately, most hardware and software resources used to teach programming and robotics are not adequate for students with visual impairment (VI). For instance, most programming environments for young students are highly visual and the commercial robotics kits were not built for people with VI. This paper...
The present paper uses the learning ability of neural networks (NN) for nonlinear systems in order to design a controller for trajectory tracking problems in wheeled mobile robots that have their kinematic constraints violated. The singular perturbation approach is used to highlight the presence of uncertainties related to the violation of the kinematic constraints and propose an alternative global...
The dynamics of complex neural networks modelling self-organized process in cortical maps, like unsupervised competitive neural networks (UCNN), are based on the standard competitive learning law to determine the best-matching representant among all neurons for a given input. However, UCNNs include aspects of long and short-term memory, which are characterized by an equation of neural activity as...
This paper describes an algorithm that performs an autonomous 3D reconstruction of an environment with a single 2D Laser Imaging Detection and Ranging (LIDAR) sensor, as well as its implementation on a mobile platform using the Robot Operating System (ROS). A ROS node was used to redirect the flow of data that can go to either the 2D Simultaneous Localization And Mapping (SLAM) ROS node or to the...
We describe and evaluate a novel optimization-based off-line path planning algorithm for mobile robots based on the Counterexample-Guided Inductive Optimization (CEGIO) technique. CEGIO iteratively employs counterexamples generated from Boolean Satisfiability (SAT) and Satisfiability Modulo Theories (SMT) solvers, in order to guide the optimization process and to ensure global optimization. This paper...
Nowadays, it is notorious the increasing use of autonomous vehicles in different outdoor field applications such as agriculture, the mining industry, environmental monitoring, among others. In this context, the determination of the traversability level of a terrain is a fundamental task for safe and efficient navigation of Autonomous Ground Vehicles (AGVs) in unstructured unknown outdoor environments...
The recent adoption of the Robot Operating System (ROS) as a software standard in robotics has contributed to novel solutions for several problems on the area. One such problem is known as Simultaneous Localization and Mapping (SLAM), for which a number of algorithms from different classes are available as ROS packages ready to be used on any compatible robot. Considering that there is often a need...
Due to the complexity of the mathematical and computational reproduction of collision movements performed by solids objects in the real world, alternately a common approach is to use dynamic models compound of elastic (spring) and dissipative (damper) forces with the theory of rigid bodies. In this paper, the modeling of translational and rotational movement of a solid cube in free fall colliding...
Due to low-cost and simplicity, differential drive mobile robot are very popular in academic and hobby environments. However, in some applications, such as robot soccer, these robots need to move quickly and aggressively, thus requiring the use of techniques from control systems theory, where an accurate mathematical model is paramount. On the other hand, given budget limitations, the components used...
The number of roundabouts has been increased as they have demonstrated improvements over unsignalized and signalized intersections regarding safety, traffic flow, access management, etc. In this sense, autonomous vehicles should satisfactorily deal with the problem of path planning at these circular intersections. Approaches proposed in literature employ optimization techniques to improve the level...
The cooperation between autonomous vehicles is receiving a growing attention from the academic literature. As a promising field, there is a need for studies that can provide both an overview and a structured analysis of the present literature. This paper presents a systematic mapping for the scenario of systems with cooperation of non-urban vehicles, presenting the steps for the accomplishment of...
This paper presents the specifications for a network architecture of a squadron of Unmanned Aerial Vehicles to be used to scan rocket impact areas. It presents the main features of communication networks for multi UAV systems and the details of its application. In this context, we propose a network architecture based on XBee Pro 900HP S3B modules integrated to a hardware platform controlled by embedded...
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