10,965 research outputs found
SANTO: Social Aerial NavigaTion in Outdoors
In recent years, the advances in remote connectivity, miniaturization of electronic components and computing power has led to the integration of these technologies in daily devices like cars or aerial vehicles. From these, a consumer-grade option that has gained popularity are the drones or unmanned aerial vehicles, namely quadrotors. Although until recently they have not been used for commercial applications, their inherent potential for a number of tasks where small and intelligent devices are needed is huge. However, although the integrated hardware has advanced exponentially, the refinement of software used for these applications has not beet yet exploited enough. Recently, this shift is visible in the improvement of common tasks in the field of robotics, such as object tracking or autonomous navigation. Moreover, these challenges can become bigger when taking into account the dynamic nature of the real world, where the insight about the current environment is constantly changing. These settings are considered in the improvement of robot-human interaction, where the potential use of these devices is clear, and algorithms are being developed to improve this situation. By the use of the latest advances in artificial intelligence, the human brain behavior is simulated by the so-called neural networks, in such a way that computing system performs as similar as possible as the human behavior. To this end, the system does learn by error which, in an akin way to the human learning, requires a set of previous experiences quite considerable, in order for the algorithm to retain the manners. Applying these technologies to robot-human interaction do narrow the gap. Even so, from a bird's eye, a noticeable time slot used for the application of these technologies is required for the curation of a high-quality dataset, in order to ensure that the learning process is optimal and no wrong actions are retained. Therefore, it is essential to have a development platform in place to ensure these principles are enforced throughout the whole process of creation and optimization of the algorithm. In this work, multiple already-existing handicaps found in pipelines of this computational gauge are exposed, approaching each of them in a independent and simple manner, in such a way that the solutions proposed can be leveraged by the maximum number of workflows. On one side, this project concentrates on reducing the number of bugs introduced by flawed data, as to help the researchers to focus on developing more sophisticated models. On the other side, the shortage of integrated development systems for this kind of pipelines is envisaged, and with special care those using simulated or controlled environments, with the goal of easing the continuous iteration of these pipelines.Thanks to the increasing popularity of drones, the research and development of autonomous capibilities has become easier. However, due to the challenge of integrating multiple technologies, the available software stack to engage this task is restricted. In this thesis, we accent the divergencies among unmanned-aerial-vehicle simulators and propose a platform to allow faster and in-depth prototyping of machine learning algorithms for this drones
AltURI: a thin middleware for simulated robot vision applications
Fast software performance is often the focus when developing real-time vision-based control applications for robot simulators. In this paper we have developed a thin, high performance middleware for USARSim and other simulators designed for real-time vision-based control applications. It includes a fast image server providing images in OpenCV, Matlab or web formats and a simple command/sensor processor. The interface has been tested in USARSim with an Unmanned Aerial Vehicle using two control applications; landing using a reinforcement learning algorithm and altitude control using elementary motion detection. The middleware has been found to be fast enough to control the flying robot as well as very easy to set up and use
An Open-Source Simulator for Cognitive Robotics Research: The Prototype of the iCub Humanoid Robot Simulator
This paper presents the prototype of a new computer simulator for the humanoid robot iCub. The iCub is a new open-source humanoid robot developed as a result of the “RobotCub” project, a collaborative European project aiming at developing a new open-source cognitive robotics platform. The iCub simulator has been developed as part of a joint effort with the European project “ITALK” on the integration and transfer of action and language knowledge in cognitive robots. This is available open-source to all researchers interested in cognitive robotics experiments with the iCub humanoid platform
Managing a Fleet of Autonomous Mobile Robots (AMR) using Cloud Robotics Platform
In this paper, we provide details of implementing a system for managing a
fleet of autonomous mobile robots (AMR) operating in a factory or a warehouse
premise. While the robots are themselves autonomous in its motion and obstacle
avoidance capability, the target destination for each robot is provided by a
global planner. The global planner and the ground vehicles (robots) constitute
a multi agent system (MAS) which communicate with each other over a wireless
network. Three different approaches are explored for implementation. The first
two approaches make use of the distributed computing based Networked Robotics
architecture and communication framework of Robot Operating System (ROS) itself
while the third approach uses Rapyuta Cloud Robotics framework for this
implementation. The comparative performance of these approaches are analyzed
through simulation as well as real world experiment with actual robots. These
analyses provide an in-depth understanding of the inner working of the Cloud
Robotics Platform in contrast to the usual ROS framework. The insight gained
through this exercise will be valuable for students as well as practicing
engineers interested in implementing similar systems else where. In the
process, we also identify few critical limitations of the current Rapyuta
platform and provide suggestions to overcome them.Comment: 14 pages, 15 figures, journal pape
System integration of a Telerobotic Demonstration System (TDS) testbed
The concept for and status of a telerobotic demonstration system testbed that integrates teleoperation and robotics is described. The components of the telerobotic system are described and the ongoing projects are discussed. The system can be divided into two sections: the autonomous subsystems, and the additional interface and support subsystems including teleoperations. The workings of each subsystem by itself and how the subsystems integrate into a complete system is discussed
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