RoboBrain: A software architecture mapping the human brain

Vasiliu, Laurenţiu; Trochidis, Ilias; Bußler, Christoph; Koumpis, Adamantios

doi:10.1109/humanoids.2014.7041353

Cited by 6 publications

(2 citation statements)

References 17 publications

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“…The RoboBrain project was launched to enable robots to share information and learn from each other through interaction with cloud servers. 5 Rapyuta framework was put forward. 6 Raptuya provides related resources for robots and optimizes task management, command data, and communication methods.…”

Section: Cloud Robotic Networkmentioning

confidence: 99%

An energy sensitive system framework for cloud robotic network

Guo

Yang

et al. 2019

Int J Communication

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Cloud robotic network (CRN) is an extension of the traditional robots, and its important significance is to use the Internet and cloud computing to overcome the limitations of single robot and enhance its computing power. As the core technology of CRN, how to achieve the full potential of computation off-loading is a critical issue. Starting from the basic models of CRN, this paper studies the network architecture and the computation off-loading method to solve this problem. Firstly, a relatively detailed system model is designed based on the characteristics of CRN to provide theoretical and quantitative basis for subsequent research. Then, based on the theory of connected dominating set, a distributed CDS construction algorithm PCDS is proposed, which provides a virtual backbone with more power for the network. Finally, an energy sensitive computation off-loading method is proposed to improve the lifetime of the whole network while ensuring the execution time and energy loss of computational tasks. Simulation results show that the proposed framework can effectively improve the performance of CRN and prolong the lifetime to a certain extent. KEYWORDSCDS, cloud robotic network, computation off-loading, energy sensitive INTRODUCTION"Robots," a concept which shows up first in science fiction films, can be seen everywhere nowadays, such as household sweeping robots, industrial assembly robots, and commercial UAVs (Unmanned Aerial Vehicles). However, due to the slow development of power technology and the limitation of robot body shape, traditional robots have some drawbacks, such as endurance capacity and computing power; hence, the function of a single robot is relatively simple, which cannot meet people's demands gradually.With the development of wireless network technology and cloud computing, cloud robots emerge at the historic moment. Cloud robots can make full use of the ubiquity of the network and enhance the capabilities of traditional robots, thus expanding the robots' application field, simplifying the development process of robotic systems and even reducing the energy cost of robots. As the core technology of CRN, computation off-loading can make robots and cloud cooperatively process tasks, which can effectively improve the performance of the robots.However, cloud robots are often highly heterogeneous, self-organizing, and weak-coupling system. There still are some problems in CRN, such as network instability and inefficient off-loading. In order to make the full use of CRN, a few challenges need to be tackled: Int J Commun Syst. 2019;32:e4028.wileyonlinelibrary.com/journal/dac

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Section: Cloud Robotic Networkmentioning

confidence: 99%

An energy sensitive system framework for cloud robotic network

Guo

Yang

et al. 2019

Int J Communication

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“…In this sense, there are currently initiatives that focus on the definition of robot architectures (e.g. Vasiliu et al [20]), that integrate distributed resources to the task, so mitigating specific constraints of the robot platform. In parallel, several research communities are engaged in the definition of ontologies for knowledge sharing, distributed learning, and the collection and reuse of information for practical applications (e.g.…”

Section: Introductionmentioning

confidence: 99%

Sensory-Motor Anticipation and Local Information Fusion for Reliable Humanoid Approach

Chame

Chevallereau

2016

New Trends in Medical and Service Robots

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The possibility of developing increasingly sophisticated robots, and the availability of cloud-connected resources, have boosted the interest in the study of real world applications of service robotics. However, in order to operate under natural or less structured conditions, and given the information processing bottleneck and the reactivity required for a secure execution of the task, it is desirable that the agent can exploit more efficiently the local information available, so that being more autonomous, and relying less on remote computation. This study explores a strategy for obtaining reliable approach tasks. It considers the anticipation of perception, by taking into account the statistical regularities and the information redundancies induced in the sensorymotor coupling. From an initial perception of the object assisted by remote computation, contextual features are defined for capturing bodily sensations emerging in the task. The observations based on proprioceptive and visual data are fused in a Bayesian Network, which is in charge of assessing the saliency during the object approach, thus constituing a local discriminative processing of the object. The strategy proposed reduces dependency on context-free models of behavior, while providing an estimate on the degree of confidence in the progress of the task.

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