Ono: an open platform for social robotics

In recent times, the focal point of research in robotics has shifted from industrial ro- bots toward robots that interact with humans in an intuitive and safe manner. This evolution has resulted in the subfield of social robotics, which pertains to robots that function in a human environment and that can communicate with humans in an int- uitive way, e.g. with facial expressions. Social robots have the potential to impact many different aspects of our lives, but one particularly promising application is the use of robots in therapy, such as the treatment of children with autism. Unfortunately, many of the existing social robots are neither suited for practical use in therapy nor for large scale studies, mainly because they are expensive, one-of-a-kind robots that are hard to modify to suit a specific need. We created Ono, a social robotics platform, to tackle these issues. Ono is composed entirely from off-the-shelf components and cheap materials, and can be built at a local FabLab at the fraction of the cost of other robots. Ono is also entirely open source and the modular design further encourages modification and reuse of parts of the platform

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

A computer integrated unified modelling approach to responsive manufacturing

Computer modelling approaches have significant potential to enable decision-making about various aspects of responsive manufacturing. In order to understand the system prior to the selection of any responsiveness strategy, multiple process segments of organisations need to be modelled. The article presents a novel systematic approach for creating coherent sets of unified enterprise, simulation and other supporting models that collectively facilitate responsiveness. In this approach, enterprise models are used to explicitly define relatively enduring relationships between (i) production planning and control (PPC) processes, that implement a particular strategy and (ii) process-oriented elements of production systems, that are work loaded by the PPC processes. Coherent simulation models, can in part be derived from the enterprise models, so that they computer execute production system behaviours. In this way, time-based performance outcomes can be simulated; so that the impacts of alternative PPC strategies on the planning and controlling historical or forecasted patterns of workflow, through (current and possible future) production system models, can be analysed. The article describes the unified modelling approach conceived and its application in a furniture industry case study small and medium enterprise (SME)

Supply chain complexity and robustness analysis

Imperial Users onl

SYSTEM MODEL FOR AUTONOMOUS ROAD FREIGHT TRANSPORTATION

Emerging info-communication and vehicle technologies (especially vehicle automation) facilitate evolvement of autonomous road freight transportation. The entire transport system and its operation undergo a major change. New service concepts are growing and the existing ones are being transformed. The changing is particularly significant in city logistics. However, there are debates about the ways of automation of processes targeting improvement of capacity utilisation and decrease of expenditures. The main research questions of the paper are therefore: what properties of the future autonomous freight transportation are presumed; what system structure is to be constructed and how the system is to be operated? After introducing the basic notions and reviews of the current systems and developments, the shifting from traditional freight transportation to autonomous system is investigated by several aspects. A system- and process-oriented analytical modelling method has been applied. The main system constituents and their connections are modelled. Finally, we elaborate the operational model of road freight transportation, which is applicable principally in metropolitan areas. In conclusion, the presented results appoint the research and innovation trends towards the automation of freight transportation