Knowledge processing is an essential technique for enabling autonomous robots to do the right thing to the right object in the right way. Using knowledge processing the robots can achieve more flexible and general behavior and better performance. While knowledge representation and reasoning has been a well-established research field in Artificial Intelligence for several decades, little work has been done to design and realize knowledge processing mechanisms for the use in the context of robotic control. In this paper, we report on KNOWROB, a knowledge processing system particularly designed for autonomous personal robots. KNOWROB is a first-order knowledge representation based on description logics that provides specific mechanisms and tools for action-centered representation, for the automated acquisition of grounded concepts through observation and experience, for reasoning about and managing uncertainty, and for fast inference — knowledge processing features that are particularly necessary for autonomous robot control.

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KNOWROB — knowledge processing for autonomous personal robots

The Internet of Robotic Things is an emerging vision that brings together pervasive sensors and objects with robotic and autonomous systems. This survey examines how the merger of robotic and Inter...

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The Internet of Robotic Things: A review of concept, added value and applications

The vision of an ecology of physically embedded intelligent systems, or PEIS-Ecology, combines insights from the fields of autonomous robotics and ambient intelligence to provide a new approach to building robotic systems in the service of people. In this paper, we present this vision, and we report the results of a four-year collaborative research project between Sweden and Korea aimed at the concrete realization of this vision.We focus in particular on three results: a robotic middleware able to cope with highly heterogeneous systems; a technique for autonomous self-configuration and reconfiguration; and a study of the problem of sharing information of both physical and digital nature.

The PEIS-Ecology project: Vision and results

A common vision in the field of autonomous robotics is to create a skilled robot companion that is able to live in our homes and perform physical tasks to help us in our everyday life. Another vision, coming from the field of ambient intelligence, is to create a network of intelligent home devices that provide us with information, communication, and entertainment. We propose to combine these two visions into the new concept of an ecology of networked Physically Embedded Intelligent Systems (PEIS). In this paper, we define this concept, and illustrate it by describing an experimental system that involves real robotic devices.

https://www.ami-conferences.org/2005/proceedings/articles_pagines/29.pdf

PEIS ecologies: ambient intelligence meets autonomous robotics

Early detection and adaptive support to changing individual needs related to ageing is an important challenge in today's society. In this paper we present a system called GiraffPlus that aims at addressing such a challenge and is developed in an on-going European project. The system consists of a network of home sensors that can be automatically configured to collect data for a range of monitoring services; a semi-autonomous telepresence robot; a sophisticated context recognition system that can give high-level and long term interpretations of the collected data and respond to certain events; and personalized services delivered through adaptive user interfaces for primary users. The system performs a range of services including data collection and analysis of long term trends in behaviors and physiological parameters (e.g. relating to sleep or daily activity); warnings, alarms and reminders; and social interaction through the telepresence robot. The latter is based on the Giraff telepresence robot, which is already in place in a number of homes. A distinctive aspect of the project is that the GiraffPlus system will be installed and evaluated in at least 15 homes of elderly people. This paper provides a general overview of the GiraffPlus system and its evaluation.

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GiraffPlus: Combining social interaction and long term monitoring for promoting independent living

Autonomous functional configuration of a network robot system

We consider an ecology of robots in which robots can help each other by offering information-producing functionalities. A functional configuration of this ecology is a way to allocate and connect functionalities among the participating robots. In general, different configurations can be used to solve the same task, depending on the current situation, and some tasks require sequences of different configurations to be solved. In this paper, we propose a plan-based approach to automatically generate a preferred configuration for a given task, environment, and set of resources. We also describe how our configuration planner can be integrated with an action planner to deal with tasks that require sequences of configurations. We illustrate these ideas on a specific instance of an ecology of robots, called a PEIS Ecology. We also show an experiment run on our PEIS Ecology testbed, in which a sequence of configurations for an olfactory task is automatically generated and executed.

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Plan-Based Configuration of an Ecology of Robots

There is a tendency today toward the study of distributed systems consisting of many heterogeneous, networked, cooperating robotic devices. We refer to a system of this type as an ecology of robots. We call functional configuration of this ecology a way to allocate and connect functionalities among its robots. In general, the same ecology can perform different tasks by using different configuration. Moreover, the same task can often be solved using different configurations, and which is the best one depends on the available resources. This potential flexibility of a robot ecology is reduced by the fact that, in most current approaches, configurations are pre-programmed by hand. In this paper, we propose a plan-based approach to automatically generate a preferred configuration of a robot ecology given a task, environment, and set of resources. In contrast to previous approaches, the state of the ecology is automatically acquired at planning time, and it is monitored during execution in order to reconfigure if a functionality fails. We illustrate these ideas on a specific instance of an ecology of robots, called PEIS Ecology. We also show an experiment run on our PEIS Ecology testbed, in which a robot needs to reconfigure when the original configuration fails.

Dynamic self-configuration of an ecology of robots

We consider groups of autonomous robots in which robots can help each other by offering information-producing functionalities. A functional configuration is a way to allocate and connect functionalities among robots. In general, different configurations can be used to solve the same task, depending on the current situation. In this paper, we define the idea of functional configuration, and we propose a plan-based approach to automatically generate a preferred configuration for a given task, environment, and set of resources. To illustrate these ideas, we show a simple experiment in which two robots mutually help each-other to cross a door.

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Robert Lundh

Papers

The PEIS-Ecology project: Vision and results

Autonomous functional configuration of a network robot system

Plan-Based Configuration of an Ecology of Robots

Dynamic self-configuration of an ecology of robots

Plan-Based Configuration of a Group of Robots