13,258 research outputs found

    Managing a Fleet of Autonomous Mobile Robots (AMR) using Cloud Robotics Platform

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    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

    Approaching delivery as a service

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    This paper explores the new logistics business model of Delivery as a Service, a concept aiming at a more efficient, fast and customer-oriented practice, linking IT solution development, urban logistics operations, supply chain efficiency and new business models. Delivery as a Service (DaaS) is defined as a service-oriented delivery and business processes in line with customer expectations and needs in the on-demand economy. The approach of this paper is an industry report based on evidence collected in multiple exploratory European projects integrating ambitious and strategic findings on Internet of Things, urban planning, consolidation centres, transport optimisation, and clean vehicle use. It contributes to a future scenario of urban logistics business models

    Unmanned Aerial Systems for Wildland and Forest Fires

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    Wildfires represent an important natural risk causing economic losses, human death and important environmental damage. In recent years, we witness an increase in fire intensity and frequency. Research has been conducted towards the development of dedicated solutions for wildland and forest fire assistance and fighting. Systems were proposed for the remote detection and tracking of fires. These systems have shown improvements in the area of efficient data collection and fire characterization within small scale environments. However, wildfires cover large areas making some of the proposed ground-based systems unsuitable for optimal coverage. To tackle this limitation, Unmanned Aerial Systems (UAS) were proposed. UAS have proven to be useful due to their maneuverability, allowing for the implementation of remote sensing, allocation strategies and task planning. They can provide a low-cost alternative for the prevention, detection and real-time support of firefighting. In this paper we review previous work related to the use of UAS in wildfires. Onboard sensor instruments, fire perception algorithms and coordination strategies are considered. In addition, we present some of the recent frameworks proposing the use of both aerial vehicles and Unmanned Ground Vehicles (UV) for a more efficient wildland firefighting strategy at a larger scale.Comment: A recent published version of this paper is available at: https://doi.org/10.3390/drones501001

    Towards Autonomous Aviation Operations: What Can We Learn from Other Areas of Automation?

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    Rapid advances in automation has disrupted and transformed several industries in the past 25 years. Automation has evolved from regulation and control of simple systems like controlling the temperature in a room to the autonomous control of complex systems involving network of systems. The reason for automation varies from industry to industry depending on the complexity and benefits resulting from increased levels of automation. Automation may be needed to either reduce costs or deal with hazardous environment or make real-time decisions without the availability of humans. Space autonomy, Internet, robotic vehicles, intelligent systems, wireless networks and power systems provide successful examples of various levels of automation. NASA is conducting research in autonomy and developing plans to increase the levels of automation in aviation operations. This paper provides a brief review of levels of automation, previous efforts to increase levels of automation in aviation operations and current level of automation in the various tasks involved in aviation operations. It develops a methodology to assess the research and development in modeling, sensing and actuation needed to advance the level of automation and the benefits associated with higher levels of automation. Section II describes provides an overview of automation and previous attempts at automation in aviation. Section III provides the role of automation and lessons learned in Space Autonomy. Section IV describes the success of automation in Intelligent Transportation Systems. Section V provides a comparison between the development of automation in other areas and the needs of aviation. Section VI provides an approach to achieve increased automation in aviation operations based on the progress in other areas. The final paper will provide a detailed analysis of the benefits of increased automation for the Traffic Flow Management (TFM) function in aviation operations

    A preliminary safety evaluation of route guidance comparing different MMI concepts

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    Ethical and Social Aspects of Self-Driving Cars

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    As an envisaged future of transportation, self-driving cars are being discussed from various perspectives, including social, economical, engineering, computer science, design, and ethics. On the one hand, self-driving cars present new engineering problems that are being gradually successfully solved. On the other hand, social and ethical problems are typically being presented in the form of an idealized unsolvable decision-making problem, the so-called trolley problem, which is grossly misleading. We argue that an applied engineering ethical approach for the development of new technology is what is needed; the approach should be applied, meaning that it should focus on the analysis of complex real-world engineering problems. Software plays a crucial role for the control of self-driving cars; therefore, software engineering solutions should seriously handle ethical and social considerations. In this paper we take a closer look at the regulative instruments, standards, design, and implementations of components, systems, and services and we present practical social and ethical challenges that have to be met, as well as novel expectations for software engineering.Comment: 11 pages, 3 figures, 2 table

    Planning for Density in a Driverless World

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    Automobile-centered, low-density development was the defining feature of population growth in the United States for decades. This development pattern displaced wildlife, destroyed habitat, and contributed to a national loss of biodiversity. It also meant, eventually, that commutes and air quality worsened, a sense of local character was lost in many places, and the negative consequences of sprawl impacted an increasing percentage of the population. Those impacts led to something of a shift in the national attitude toward sprawl. More people than ever are fluent in concepts of “smart growth,” “new urbanism,” and “green building,” and with these tools and others, municipalities across the country are working to redevelop a central core, rethink failing transit systems, and promote pockets of density. Changing technology may disrupt this trend. Self-driving vehicles are expected to be widespread within the next several decades. Those vehicles will likely reduce congestion, air pollution, and deaths, and free up huge amounts of productive time in the car. These benefits may also eliminate much of the conventional motivation and rationale behind sprawl reduction. As the time-cost of driving falls, driverless cars have the potential to incentivize human development of land that, by virtue of its distance from settled metropolitan areas, had been previously untouched. From the broader ecological perspective, each human surge into undeveloped land results in habitat destruction and fragmentation, and additional loss of biological diversity. New automobile technology may therefore usher in better air quality, increased safety, and a significant threat to ecosystem health. Our urban and suburban environments have been molded for centuries to the needs of various forms of transportation. The same result appears likely to occur in response to autonomous vehicles, if proactive steps are not taken to address their likely impacts. Currently, little planning is being done to prepare for driverless technology. Actors at multiple levels, however, have tools at their disposal to help ensure that new technology does not come at the expense of the nation’s remaining natural habitats. This Article advocates for a shift in paradigm from policies that are merely anti-car to those that are pro-density, and provides suggestions for both cities and suburban areas for how harness the positive aspects of driverless cars while trying to stem the negative. Planning for density regardless of technology will help to ensure that, for the world of the future, there is actually a world
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