Vertical transportation in buildings

Nowadays, the building industry and its associated technologies are experiencing a period of rapid growth, which requires an equivalent growth regarding technologies in the field of vertical transportation. Therefore, the installation of synchronised elevator groups in modern buildings is a common practice in order to govern the dispatching, allocation and movement of the cars shaping the group. So, elevator control and management has become a major field of application for Artificial Intelligence approaches. Methodologies such as fuzzy logic, artificial neural networks, genetic algorithms, ant colonies, or multiagent systems are being successfully proposed in the scientific literature, and are being adopted by the leading elevator companies as elements that differentiate them from their competitors. In this sense, the most relevant companies are adopting strategies based on the protection of their discoveries and inventions as registered patents in different countries throughout the world. This paper presents a comprehensive state of the art of the most relevant recent patents on computer science applied to vertical transportationConsejería de Innovación, Ciencia y Empresa, Junta de Andalucía P07-TEP-02832, Spain

Advanced transport operating system software upgrade: Flight management/flight controls software description

The Flight Management/Flight Controls (FM/FC) software for the Norden 2 (PDP-11/70M) computer installed on the NASA 737 aircraft is described. The software computes the navigation position estimates, guidance commands, those commands to be issued to the control surfaces to direct the aircraft in flight based on the modes selected on the Advanced Guidance Control System (AGSC) mode panel, and the flight path selected via the Navigation Control/Display Unit (NCDU)

The 2014 International Planning Competition: Progress and Trends

We review the 2014 International Planning Competition (IPC-2014), the eighth in a series of competitions starting in 1998. IPC-2014 was held in three separate parts to assess state-of-the-art in three prominent areas of planning research: the deterministic (classical) part (IPCD), the learning part (IPCL), and the probabilistic part (IPPC). Each part evaluated planning systems in ways that pushed the edge of existing planner performance by introducing new challenges, novel tasks, or both. The competition surpassed again the number of competitors than its predecessor, highlighting the competition’s central role in shaping the landscape of ongoing developments in evaluating planning systems

Learning in Multi-Agent Information Systems - A Survey from IS Perspective

Multiagent systems (MAS), long studied in artificial intelligence, have recently become popular in mainstream IS research. This resurgence in MAS research can be attributed to two phenomena: the spread of concurrent and distributed computing with the advent of the web; and a deeper integration of computing into organizations and the lives of people, which has led to increasing collaborations among large collections of interacting people and large groups of interacting machines. However, it is next to impossible to correctly and completely specify these systems a priori, especially in complex environments. The only feasible way of coping with this problem is to endow the agents with learning, i.e., an ability to improve their individual and/or system performance with time. Learning in MAS has therefore become one of the important areas of research within MAS. In this paper we present a survey of important contributions made by IS researchers to the field of learning in MAS, and present directions for future research in this area

Light-based nonverbal signaling with passive demonstrations for mobile service robots

With emerging applications in robotics that have the potential to bring them into our daily lives, it is expected for them to not only operate in close proximity to humans but also interact with them as well. When operating in crowded, human-populated environments there are many communication challenges faced by robots due to variable levels of interactions (e.g. asking for help, giving information, or navigating near humans). A crucial factor for success in these interactions is a robot’s ability to express information about their intent, actions, and knowledge to co-located humans. Many of the robot platforms developed for service roles have non-anthropomorphic form factors in order to simplify and tailor them to their jobs. Due to a lack of anthropomorphic features, these types of robots primarily communicate using an on-screen display and/or spoken language. To overcome the limitation of not communicating as people do, we explore the viability of nonverbal light-based signals as a communication modality for mobile service robots. These types of signals have many benefits over existing modalities which they can either complement or replace when appropriate, such as having long-range visibility and persisting over time. We present a novel light-based signal control architecture implemented as a custom Robot Operating System (ROS) software package generalized to allow for various signal implementations. We implement our framework on a BWIBot, an autonomous mobile service robot created as part of the Building-Wide Intelligence Project, and evaluate its validity through a real-world user study on the scenario where a robot and human are traversing a shared corridor from opposite ends, and the potential conflict created when their paths meet. Our results demonstrate that exposing users to the robot’s use of an animated light signal only once prior to when it is information critical for the user is sufficient to disambiguate its meaning, and thus greatly enhances its utility in-situ, with no direct instruction or training to the user. These findings suggest a paradigm of passive demonstration of light-based signals in future applications.Computer Science