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Outline

Title
Abstract
Introduction
Approach and Related Work
Related Work
Transformation Procedure
Overall Procedure Skeleton
Recording Future Events
Analysis and Discussion
Analysis
Discussion
Conclusion and Future Work
Conclusion
Future Work
References

Self-Maintaining and Self-Monitoring Autonomous Systems

Profile image of Andreas WortmannAndreas Wortmann

2010

Abstract

To arrive at truly intelligent agents such as robots, many issues need to be addressed such as perception, locomotion, manipulation, human-robot interaction, planning and reasoning. In this thesis we are concerned with the latter in the sense of cognitive robotics as introduced by the late Ray Reiter, meaning “the study of the knowledge representation and reasoning problems faced by an autonomous robot (or agent) in a dynamic and incompletely known world”(Levesque and Lakemeyer (2008)).

Related papers

Cognitive Robotics - Towards the Development of Next-Generation Robotics and Intelligent Systems
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Springer eBooks, 2022

In this paper we make the case for cognitive robotics, that we consider a prerequisite for next generation systems. We give a brief account of current cognition-enabled systems, and viable cognitive architectures, discuss system requirements that are currently not sufficiently addressed, and put forward our position and hypotheses for the development of next-generation, AI-enabled robotics and intelligent systems.

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Cognitive Robotics Systems
Mustafa Erden

Journal of Intelligent & Robotic Systems, 2015

While current robotic systems are getting closer to repeating a carefully-coded set of actions, they are still far from human's versatility and adaptivity. Cognitive Robotics Systems (CRS) need to reach a level of cognition that will allow them to understand and effectively operate in household and industrial environments, interact with humans, and adapt their actions to an ever growing range of situations. They are expected to be able to predict the perceptual changes that result as a consequence of human actions and replicate human activities, taking into consideration their

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A theory and implementation of cognitive mobile robots
D. Nardi

Journal of Logic and Computation, 1999

We describe an approach to reasoning agents which is based on a formal theory of actions and is actually implemented on a mobile robot working in an office environment. From an epistemological viewpoint, our proposal is originated by the correspondence between Dynamic Logics and Description Logics. Specifically, we consider an epistemic extension of Description Logics to provide a new theoretical framework for the representation of dynamic systems, where the agent's reasoning is based on its knowledge about the world. In this setting, we obtain a weaker notion of logical inference, thus simplifying the reasoning task. From a practical viewpoint, we use a general purpose knowledge representation system based on Description Logics and its associated reasoning tools, in order to plan the actions of the mobile robot 'Tino', starting from the knowledge about the environment and the action specification. In addition, we exploit the robot's capabilities in order to integrate the execution of the plan with reactive behaviours, thus enabling the agent to accomplish its tasks in the real world.

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Cognitive Robotics: Analysis of Preconditions and Implementation of a Cognitive Robotic System for Navigation Tasks
Marco Ragni

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Cognitive robotics is a fascinating field in its own right and comprises both key features of autonomicity and cognitive skills like learning behavior. Cognitive architectures aim at mirroring human memory and assumptions about mental processes. A robot does not only extend the cognitive architecture regarding real-world interaction but brings new and important challenges regarding perception and action processes. Cognitive robotics is a step towards embodied cognition and may have influences not only on cognitive science but on robotics as well. This paper presents an integration of the cognitive architecture ACT-R on a simple but programmable robotic system. This system is evaluated on a navigation experiment.

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Artificial cognitive functions towards AI-enabled collaborative robots
Evi Zouganeli

Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments

In this paper we discuss work in progress and our approach to next generation robotics. The use of cognitive architectures can overcome some of the challenges encountered when Artificial Intelligence (AI) algorithms are introduced to robotic systems. New cognitive functionality is required to that end. We discuss system requirements that are currently not sufficiently addressed, and present our current work. CCS CONCEPTS • Computing methodologies → Cognitive robotics; Artificial intelligence.

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Cognitive Robotics: For Never was a Story of More Owe than This
Emanuel Diamant

2014

We are now on the verge of the next technical revolutionrobots are going to invade our lives. However, to interact with humans or to be incorporated into a human "collective" robots have to be provided with some human-like cognitive abilities. What does it mean?-Nobody knows. But, robotics research communities are trying hard to find out a way to cope with this problem. Meanwhile, despite abundant funding these efforts did not lead to any meaningful result (only in Europe, only in the past ten years, Cognitive Robotics research funding has reached a ceiling of 1.39 billion euros). In the next ten years, a similar budget is going to be spent to tackle the Cognitive Robotics problems in the frame of the Human Brain Project. There is no reason to expect that this time the result will be different. We would like to try to explain why we are so unhappy about this.

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Perceptions or Actions? Grounding How Agents Interact Within a Software Architecture for Cognitive Robotics
Pablo Bustos

Cognitive Computation, 2019

One of the aims of cognitive robotics is to endow robots with the ability to plan solutions for complex goals and then to enact those plans. Additionally, robots should react properly upon encountering unexpected changes in their environment that are not part of their planned course of actions. This requires a close coupling between deliberative and reactive control flows. From the perspective of robotics, this coupling generally entails a tightly integrated perceptuomotor system, which is then loosely connected to some specific form of deliberative system such as a planner. From the high-level perspective of automated planning, the emphasis is on a highly functional system that, taken to its extreme, calls perceptual and motor modules as services when required. This paper proposes to join the perceptual and acting perspectives via a unique representation where the responses of all software modules in the architecture are generalized using the same set of tokens. The proposed representation integrates symbolic and metric information. The proposed approach has been successfully tested in CLARC, a robot that performs Comprehensive Geriatric Assessments of elderly patients. The robot was favourably appraised in a survey conducted to assess its behaviour. For instance,

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MLR (Memory, Learning and Recognition): A General Cognitive Model - applied to Intelligent Robots and Systems Control
Aras Dargazany

ArXiv, 2019

This paper introduces a new perspective of intelligent robots and systems control. The presented and proposed cognitive model: Memory, Learning and Recognition (MLR), is an effort to bridge the gap between Robotics, AI, Cognitive Science, and Neuroscience. The currently existing gap prevents us from integrating the current advancement and achievements of these four research fields which are actively trying to define intelligence in either application-based way or in generic way. This cognitive model defines intelligence more specifically, parametrically and detailed. The proposed MLR model helps us create a general control model for robots and systems independent of their application domains and platforms since it is mainly based on the dataset provided for robots and systems controls. This paper is mainly proposing and introducing this concept and trying to prove this concept in a small scale, firstly through experimentation. The proposed concept is also applicable to other differe...

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A cognitive architecture for robot self-consciousness
Salvatore Gaglio

Artificial Intelligence in Medicine, 2008

One of the major topics towards robot consciousness is to give a robot the capabilities of self-consciousness. We propose that robot self-consciousness is based on higher order perception of the robot, in the sense that first order robot perception is the immediate perception of the outer world, while higher order perception is the perception of the inner world of the robot. Methods and Material: We refer to a robot cognitive architecture that has been developed during almost ten years at the RoboticsLab of the University of Palermo. The architecture is organized in three computational areas. The subconceptual area is concerned with the low level processing of perceptual data coming from the

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Long Term Requirements for Cognitive Robotics
Jeremy L Wyatt

2006

This paper discusses some of the long term objectives of cognitive robotics and some of the requirements for meeting those objectives that are still a very long way off. These include requirements for visual perception, for architectures, for kinds of learning, and for innate competences needed to drive learning and development in a variety of different environments. The work arises mainly out of research on requirements for forms of representation and architectures within the PlayMate scenario, which is a scenario concerned with a robot that perceives, interacts with and talks about 3-D objects on a tabletop, one of the scenarios in the EC-funded CoSy Robotics project.

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Toward cognitive robotics
John Laird

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Our long-term goal is to develop autonomous robotic systems that have the cognitive abilities of humans, including communication, coordination, adapting to novel situations, and learning through experience. Our approach rests on the recent integration of the Soar cognitive architecture with both virtual and physical robotic systems. Soar has been used to develop a wide variety of knowledge-rich agents for complex virtual environments, including distributed training environments and interactive computer games. For development and testing in robotic virtual environments, Soar interfaces to a variety of robotic simulators and a simple mobile robot. We have recently made significant extensions to Soar that add new memories and new non-symbolic reasoning to Soar's original symbolic processing, which should significantly improve Soar abilities for control of robots. These extensions include episodic memory, semantic memory, reinforcement learning, and mental imagery. Episodic memory and semantic memory support the learning and recalling of prior events and situations as well as facts about the world. Reinforcement learning provides the ability of the system to tune its procedural knowledgeknowledge about how to do things. Mental imagery supports the use of diagrammatic and visual representations that are critical to support spatial reasoning. We speculate on the future of unmanned systems and the need for cognitive robotics to support dynamic instruction and taskability.

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