The robots of tomorrow should be endowed with the ability to adapt to drastic and unpredicted changes in their environment and interactions with humans. Such adaptations, however, cannot be boundless: the robot must stay trustworthy. So, the adaptations should not be just a recovery into a degraded functionality. Instead, they must be true adaptations: the robot must change its behaviour while maintaining or even increasing its expected performance and staying at least as safe and robust as before. The RoboSAPIENS project will focus on autonomous robotic software adaptations and will lay the foundations for ensuring that they are carried out in an intrinsically trustworthy, safe and efficient manner, thereby reconciling open-ended self-adaptation with safety by design. RoboSAPIENS will transform these foundations into ‘first time right’-design tools and platforms and will validate and demonstrate them.

Efficient algorithm integration is a key issue in aerial robotics. However, only a few integration solutions rely on a cognitive approach. Cognitive approaches break down complex problems into independent units that may deal with progressively lower-level data interfaces, all the way down to sensors and actuators. A cognitive architecture defines information flow among units to produce emergent intelligent behavior. Despite the improvements in autonomous decision-making, several key issues remain open. One of these issues is the selection, coordination, and decision-making related to the several specialized tasks required for fulfilling mission objectives. This work addresses decision-making for the cognitive unmanned-aerial-vehicle architecture coined as ARCog. The proposed architecture lays the groundwork for the development of a software platform aligned with the requirements of the state-of-the-art technology in the field. The system is designed to provide high-level decision-making. Experiments prove that ARCog works correctly in its target scenario.

This paper introduces an approach of collaborative control for individual robots to collaboratively perform a common task, without the need for a centralized controller to coordinate the group. The approach is illustrated by an application example involving multiple robots performing a collaborative task to achieve a common goal. The objective of this example problem is to control multiple robots that are connected to an object through elastic cables in order to bring the object to a target position. There is no communication between the robots, and hence each robot is unaware of how the other robots are going to react at any instant. Only the information pertaining to the object and the target is available to all the robots at any instant. Genetic fuzzy system (GFS) is used to develop controller for each of the robots. The nonlinearity of fuzzy logic systems coupled with the search capability of genetic algorithms provides a tool to design controllers for such collaborative tasks. A set of training scenarios are developed to train the individual robot controllers for this task. The trained controllers are then tested on an extensive set of scenarios. This paper describes the development process of GFS controllers for dynamic case involving systems consisting of three robots. It is also shown that the GFS controllers are scalable for the more complex systems involving more than three robots.

New generations of distributed systems are opening novel perspectives for logic programming (LP): On the one hand, service-oriented architectures represent nowadays the standard approach for distributed systems engineering; on the other hand, pervasive systems mandate for situated intelligence. In this paper, we introduce the notion of Logic Programming as a Service (LPaaS) as a means to address the needs of pervasive intelligent systems through logic engines exploited as a distributed service. First, we define the abstract architectural model by re-interpreting classical LP notions in the new context; then we elaborate on the nature of LP interpreted as a service by describing the basic LPaaS interface. Finally, we show how LPaaS works in practice by discussing its implementation in terms of distributed tuProlog engines, accounting for basic issues such as interoperability and configurability.

The world of intelligent and interactive systems is undergoing an era of unprecedented innovation and advanced development. With the rapid progress in natural sensing and perceptual computing technologies, devices and machines are increasingly being endowed with the abilities to sense and understand the world, navigate in the environment, and interact with humans in natural ways. Interfaces based on touch sensing and speech recognition are now ubiquitous, and the race is on to the next frontiers of machine intelligence and interactions based on three-dimensional (3D) sensing. In this paper, we review the recent progress in the development of real-time 3D-sensing technologies and their deployment in a new class of interactive and autonomous systems. As an example of a commercially available platform, we describe the Intel® RealSense technologies, as well as its deployments in a new class of interactive and autonomous systems and applications.

This paper describes the Robotics and Intelligent Systems Program (RISP) at the Oak Ridge National Laboratory (ORNL). RISP is a focal point at ORNL for studies in robotics, teleoperations, and related aspects of intelligent machines, such as artificial intelligence, neural networks, and parallel computing. RISP research is intended to minimize human error through automation of repetitive, dull, and routine tasks; to minimize human risk by allowing effective remote operation in hazardous environments; to optimize cooperation of humans and machines; and to cope effectively with emergency situations where fast response is essential.

While the use of mobile devices for language learning has sparked the interest of an increasing number of researchers in recent years (e.g., Aizawa & Kiernan, 2003; Thornton & Houser, 2005), our knowledge of learners' preferences for the mobile platform and their usage patterns remains limited. Are learners prepared to use mobile phones for performing language learning activities, or is there still a preference for desktop computer environments? Do learners make attempts to use mobile phones and then opt for a desktop computer instead? When and where do those learners who choose to use mobile phones use them, and why do they choose them? The current study investigated 75 learners of English at a Japanese university who were assigned vocabulary learning activities which they could choose to complete on either a mobile phone or desktop computer. It sought to determine their intentions to use mobile phones for language learning if other options were available, to compare this with their actual usage patterns, and to determine when and why learners used mobile phones. Learner attitudes and preferences were elicited through a post-survey, and usage patterns were determined through analysis of detailed server logs. The results are discussed in terms of the readiness of learners to undertake mobile-based language learning activities, and the issues having an effect on the establishment of the mobile phone as a language learning tool.

Considering manufacturing expertise during the early stages of design can be of great benefit. Such information can greatly improve not only the quality of a design, but it can also ensure the generation of an easily manufactured design. This, in turn, can lower the final cost of the designed product. By evaluating how easily an evolving conceptual design can be made, potential hazards can be avoided before any detailed design efforts commence. The conceptual manufacturing planning requisite to such an evaluation is the focus of this paper. A domain-independent strategy for conceptual manufacturing planning is presented. A task-structure analysis of this strategy shows its domain independence. A specific implementation of this strategy for polymer composites manufacturing planning (Socharis) is discussed. The high-level implementation details of Socharis are presented as instantiations of the conceptual manufacturing planning strategy. Finally, the validity of the planning strategy and the utility of Socharis are assessed.