A comparison between a person and a robot in the attention, imitation, and repetitive and stereotypical behaviors of children with autism spectrum disorder.

The aim of the present study was to assess the usefulness of QT, a socially assistive robot, in interventions with children with autism spectrum disorder (ASD) by assessing children’s attention, imitation, and presence of repetitive and stereotyped behaviors. Fifteen children diagnosed with ASD, aged from 4 to 14 years participated in two short interactions, one with a person and one with QT robot. Statistical analyses revealed that children directed more attention towards the robot than to the person, imitated the robot as much as the person, and engaged in fewer repetitive or stereotyped behaviors with the robot than with the person. These results support previous research demonstrating the usefulness of robots in interventions with children with ASD and provide new evidence to the usefulness of robots in reducing repetitive and stereotyped behaviors in children with ASD, which can affect children’s learning

Reasoning on Robot Knowledge from Discrete and Asynchronous Observations

Robot knowledge of the world is created from discrete and asynchronous events received from its perception components. Proper representation and maintenance of robot knowledge is crucial to enable the use of robot knowledge for planning, user-interaction, etc. This paper identifies some of the main issues related to the representation, maintenance and querying of robot knowledge based on discrete asynchronous events such as event-history management and synchronization, and introduces a language for simplifying developers’ job at making a suitable representation of robot knowledge

Plexil-Like Plan Execution Control in Agent Programming

BDI-based agent programming languages are well-known technologies for implementing autonomous agents in dynamic environments. Supporting robot programming however requires the plan representation and execution control capabilities of these languages to be extended for 1-) controlling and monitoring the execution of actions in complex arrangements and 2-) coordinating the parallel execution of plans over shared resources. To this end, this paper adapts and extends PLEXIL, an expressive and well-defined robotic plan execution language, for plan representation and execution in BDI-based agent programming languages. The syntax and semantics of the new language is presented and its integration in operational semantics of BDI-based agent programming languages is discussed

Information Engineering in Autonomous Robot Software

In order to engage and help in our daily life, autonomous robots are to operate in dynamic and unstructured environments and interact with people. As the robot's environment and its behaviour are getting more complex, so are the robot's software and the knowledge that the robot needs to carry out its operations. In collaborating with a human to bake a cake, for instance, the robot needs a large number of components to perceive and manipulate the objects and to communicate and coordinate the task with the human. It also needs a large body of knowledge such as the cooking instruction, the model of objects and common-sense knowledge such as, “eggs are usually found in the fridge.” To cope with such complexity, there has been a large body of research on robotic frameworks and robotic knowledge representation and reasoning systems. Robotic frameworks increase the re-usability of the robot's software by supporting its decomposition into separate components and supporting the configuration, composition, communication and coordination of the components. Robotic knowledge representation and reasoning systems provide common language structures and tools to represent, share and integrate pieces of knowledge and to reason about it. However, there is a lack of tools and mechanisms to support aggregating and correlating sensory data to extract knowledge of the robot's environment and to manage, update and query such changing knowledge in an efficient way. The robot's sensory components continuously and asynchronously process its sensory data into events, discrete pieces of information. Information engineering is the processing, management and querying of sensory events to create and use knowledge of the robot's environment. To be responsive to the situations of the environment, flows of sensory events should be processed on the fly to detect the occurrence of complex events (i.e. on-flow processing). Also, some information should be extracted and maintained in memory to query the state of the environment in the past (i.e. on-demand processing). In addition, planning and plan execution requires the repeated evaluation of the same queries. Doing so efficiently requires an incremental approach to update the results of these queries when the robot’s knowledge base is updated (i.e. incremental query evaluation). The focus of this thesis is on supporting these three models of information processing in autonomous robot software. This thesis builds on top of recent advances in logic programming to provide a novel architecture for robotic information engineering. It develops the Retalis language for a high-level and efficient implementation of information engineering functionalities. Based on logic programming, Retalis supports rule-based representation and reasoning about knowledge in all three models of information processing. In particular, Retalis addresses the problem of processing discrete and asynchronous flows of sensory data to efficiently extract, represent and manage the robot's knowledge of the state of the environment which is frequently updated through perception and queried for planning and plan execution. We discuss how Retalis can be used to develop a novel agent-based language for autonomous robot programming and present the design specification of such a language

Fast Prototyping and Deployment of Context-Aware Smart Outdoor Environments

The article describes a tool for the fast prototyping and deployment of context-aware applications, in particular to welcome visitors in urban areas. The system has been conceived to guarantee continuous access to everybody, everywhere, at any time, and therefore it does not rely on any special device to connect visitors to the intelligent environment. In fact, we assume that visitors are equipped with low-end mobile phones embedded with bluetooth technology, which provide approximate positioning information. In spite of this, the system must be able to assess the current context in terms of user location, preferences, current activity, and to suggest city-tours and activities which meets the most the visitor's expectations. The article shows how, basing on Google maps API and OWLDL ontologies, the rapid prototyping and rapid deployment of outdoor context-aware applications based on bluetooth messaging and positioning information can be achieved

Compliance in Resource-based Process Models

Execution of business processes often requires resources, the use of which is usually subject to constraints. In this paper, we study the compliance of business processes with resource usage policies. To this end, we relate the execution of a business process to its resource requirements in terms of resources consumed, produced or blocked by tasks of the business process. Policies specifying constraints on resource usage are specified in the form of obligations and the verification of whether a business process complies with a given resource usage policy is formally studied

Agent Programming Languages Requirements for Programming Cognitive Robots (extended abstract)

This paper presents various requirements for BDI-based agent programming languages to provide better support for implementing autonomous robotic control systems. Examples of such requirements are: 1- Built-in support for integration with existing robotic frameworks such as ROS, 2- Real-time reactivity to events, 3- Management of heterogeneous sensory data and reasoning on complex events, and 4- Representation of complex plans and coordination of the parallel execution of plans

Event-processing in Autonomous Robot Programming

When implementing the high-level control component of an autonomous robot, one needs to process events, generated by sensory components, to extract the information relevant to the control component. This paper discusses the lack of support for event-processing when current agent programming languages (APLs) are used to implement the control component of autonomous robots. To address this issue, the use of information flow processing (IFP) systems is proposed to support the development of event-processing components (EPCs) for an autonomous robot. The necessary interaction mechanisms between a control component and EPCs are defined. These mechanisms allow run-time subscription to events of interest, asynchronous reception of events, maintaining necessary histories of events and run-time querying of the histories. Several implementation-related concerns for these interaction mechanisms are discussed