191 research outputs found
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
DESIGNING DISTRIBUTED CONTROLLING TESTBED SYSTEM FOR SUPPLY CHAIN AND LOGISTICS IN AUTOMOTIVE INDUSTRY
The arrival of the era of autonomous robots is indisputable. In this paper, innovations in the distributed control systems realized by autonomous guided vehicles in the automotive industry are provided as proof of concept. The main goal of the considered distributed control system design is to bring all-in-one dependent and independent VDA 5050 compliant robots that are easily configurable and manageable with the web-based high-quality user interface responsive business-critical application. Special attention is paid to applying a platform to manage all autonomous IoT based robots in one seamless system. In addition, a "single point of truth" as one of the main issues of modern distributed controlled systems has been considered.
Sen3Bot Net: a meta-sensors network to enable smart factories implementation
In the near future, an increasing number of mobile agents working closely with human operators is envisaged in smart factories. In industrial human-shared environments that employ traditional Automated Guided Vehicles, safety can be ensured thanks to the support provided by Autonomous Mobile Robots, acting as a net of meta-sensors. The localization and perception information of each meta-sensor is shared among all mobile platforms. In particular, the information about the dynamic detection of human presence is combined and uploaded in a shared map, increasing the awareness of the mobile robots about their surroundings in a specific working area.
This paper proposes an architecture that integrates the meta-sensors with an existing net of Automated Guided Vehicles, with the aim of enhancing systems based on outdated mobile agents that seek for Industry 4.0 solutions without the necessity of a complete renewal. Simulations of test scenarios are provided in order to confirm the validity of the proposed architecture model
Internet of Robotic Things Intelligent Connectivity and Platforms
The Internet of Things (IoT) and Industrial IoT (IIoT) have developed rapidly in the past few years, as both the Internet and “things” have evolved significantly. “Things” now range from simple Radio Frequency Identification (RFID) devices to smart wireless sensors, intelligent wireless sensors and actuators, robotic things, and autonomous vehicles operating in consumer, business, and industrial environments. The emergence of “intelligent things” (static or mobile) in collaborative autonomous fleets requires new architectures, connectivity paradigms, trustworthiness frameworks, and platforms for the integration of applications across different business and industrial domains. These new applications accelerate the development of autonomous system design paradigms and the proliferation of the Internet of Robotic Things (IoRT). In IoRT, collaborative robotic things can communicate with other things, learn autonomously, interact safely with the environment, humans and other things, and gain qualities like self-maintenance, self-awareness, self-healing, and fail-operational behavior. IoRT applications can make use of the individual, collaborative, and collective intelligence of robotic things, as well as information from the infrastructure and operating context to plan, implement and accomplish tasks under different environmental conditions and uncertainties. The continuous, real-time interaction with the environment makes perception, location, communication, cognition, computation, connectivity, propulsion, and integration of federated IoRT and digital platforms important components of new-generation IoRT applications. This paper reviews the taxonomy of the IoRT, emphasizing the IoRT intelligent connectivity, architectures, interoperability, and trustworthiness framework, and surveys the technologies that enable the application of the IoRT across different domains to perform missions more efficiently, productively, and completely. The aim is to provide a novel perspective on the IoRT that involves communication among robotic things and humans and highlights the convergence of several technologies and interactions between different taxonomies used in the literature.publishedVersio
Robots learn to behave: improving human-robot collaboration in flexible manufacturing applications
L'abstract è presente nell'allegato / the abstract is in the attachmen
On Multi-Agent Coordination of Agri-Robot Fleets
International audienc
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