| 1. |
- Bacciu, Davide, et al.
(författare)
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An ambient intelligence approach for learning in smart robotic environments
- 2019
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Ingår i: Computational intelligence. - : Wiley-Blackwell. - 0824-7935 .- 1467-8640. ; 35:4, s. 1060-1087
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Tidskriftsartikel (refereegranskat)abstract
- Smart robotic environments combine traditional (ambient) sensing devices and mobile robots. This combination extends the type of applications that can be considered, reduces their complexity, and enhances the individual values of the devices involved by enabling new services that cannot be performed by a single device. To reduce the amount of preparation and preprogramming required for their deployment in real-world applications, it is important to make these systems self-adapting. The solution presented in this paper is based upon a type of compositional adaptation where (possibly multiple) plans of actions are created through planning and involve the activation of pre-existing capabilities. All the devices in the smart environment participate in a pervasive learning infrastructure, which is exploited to recognize which plans of actions are most suited to the current situation. The system is evaluated in experiments run in a real domestic environment, showing its ability to proactively and smoothly adapt to subtle changes in the environment and in the habits and preferences of their user(s), in presence of appropriately defined performance measuring functions.
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| 2. |
- Bacciu, Davide, et al.
(författare)
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Learning context-aware mobile robot navigation in home environments
- 2014
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Ingår i: IISA 2014. - New York : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 57-62
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Konferensbidrag (refereegranskat)abstract
- We present an approach to make planning adaptive in order to enable context-aware mobile robot navigation. We integrate a model-based planner with a distributed learning system based on reservoir computing, to yield personalized planning and resource allocations that account for user preferences and environmental changes. We demonstrate our approach in a real robot ecology, and show that the learning system can effectively exploit historical data about navigation performance to modify the models in the planner, without any prior information oncerning the phenomenon being modeled. The plans produced by the adapted CL fail more rarely than the ones generated by a non-adaptive planner. The distributed learning system handles the new learning task autonomously, and is able to automatically identify the sensorial information most relevant for the task, thus reducing the communication and computational overhead of the predictive task.
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| 3. |
- Bontempi, Gianluca, et al.
(författare)
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The CLAIRE COVID-19 initiative : approach, experiences and recommendations
- 2021
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Ingår i: Ethics and Information Technology. - : Springer. - 1388-1957 .- 1572-8439. ; 23:Suppl. 1, s. 127-133
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Tidskriftsartikel (refereegranskat)abstract
- A volunteer effort by Artificial Intelligence (AI) researchers has shown it can deliver significant research outcomes rapidly to help tackle COVID-19. Within two months, CLAIRE's self-organising volunteers delivered the World's first comprehensive curated repository of COVID-19-related datasets useful for drug-repurposing, drafted review papers on the role CT/X-ray scan analysis and robotics could play, and progressed research in other areas. Given the pace required and nature of voluntary efforts, the teams faced a number of challenges. These offer insights in how better to prepare for future volunteer scientific efforts and large scale, data-dependent AI collaborations in general. We offer seven recommendations on how to best leverage such efforts and collaborations in the context of managing future crises.
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| 4. |
- Dragone, Mauro, et al.
(författare)
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A cognitive robotic ecology approach to self-configuring and evolving AAL systems
- 2015
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Ingår i: Engineering applications of artificial intelligence. - : Pergamon-Elsevier Science. - 0952-1976 .- 1873-6769. ; 45, s. 269-280
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Tidskriftsartikel (refereegranskat)abstract
- Robotic ecologies are systems made out of several robotic devices, including mobile robots, wireless sensors and effectors embedded in everyday environments, where they cooperate to achieve complex tasks. This paper demonstrates how endowing robotic ecologies with information processing algorithms such as perception, learning, planning, and novelty detection can make these systems able to deliver modular, flexible, manageable and dependable Ambient Assisted Living (AAL) solutions. Specifically, we show how the integrated and self-organising cognitive solutions implemented within the EU project RUBICON (Robotic UBIquitous Cognitive Network) can reduce the need of costly pre-programming and maintenance of robotic ecologies. We illustrate how these solutions can be harnessed to (i) deliver a range of assistive services by coordinating the sensing & acting capabilities of heterogeneous devices, (ii) adapt and tune the overall behaviour of the ecology to the preferences and behaviour of its inhabitants, and also (iii) deal with novel events, due to the occurrence of new user's activities and changing user's habits.
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| 5. |
- Klasson, Marcus
(författare)
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Fine-Grained and Continual Visual Recognition for Assisting Visually Impaired People
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In recent years, computer vision-based assistive technologies have enabled visually impaired people to use automatic visual recognition on their mobile phones. These systems should be capable of recognizing objects on fine-grained levels to provide the user with accurate predictions. Additionally, the user should have the option to update the system continuously to recognize new objects of interest. However, there are several challenges that need to be tackled to enable such features with assistive vision systems in real and highly-varying environments. For instance, fine-grained image recognition usually requires large amounts of labeled data to be robust. Moreover, image classifiers struggle with retaining performance of previously learned abilities when they are adapted to new tasks. This thesis is divided into two parts where we address these challenges. First, we focus on the application of using assistive vision systems for grocery shopping, where items are naturally structured based on fine-grained details. We demonstrate how image classifiers can be trained with a combination of natural images and web-scraped information about the groceries to obtain more accurate classification performance compared to only using natural images for training. Thereafter, we bring forward a new approach for continual learning called replay scheduling, where we select which tasks to replay at different times to improve memory retention. Furthermore, we propose a novel framework for learning replay scheduling policies that can generalize to new continual learning scenarios for mitigating the catastrophic forgetting effect in image classifiers. This thesis provides insights on practical challenges that need to be addressed to enhance the usefulness of computer vision for assisting the visually impaired in real-world scenarios.
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| 6. |
- Vermesan, Ovidiu, et al.
(författare)
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Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
- 2017
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Ingår i: Cognitive Hyperconnected Digital Transformation. - : River Publishers. - 9788793609112 - 9788793609105 ; , s. 97-155
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Bokkapitel (refereegranskat)abstract
- The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications.
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