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Buddy: A Companion Robot for the Whole Family

Authors:
  • Blue Frog Robotics

Abstract and Figures

Buddy with its 60 centimeters and 4 degrees of freedom is a highly engaging social robot. Buddy deploys many assets for social interaction such as its appealing design, its anthropomorphic face able to display emotional reactions and its ability to be proactive to look for a user and propose activities.Buddy is developed by Blue Frog Robotics, a French start-up based in Paris, and aims to be the friendly companion for the whole family. With its intuitive SDK based on the famous UNITY game engine, Buddy is also designed to be a tool for research and education.
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... Based on some research on object tracking robots such as Masaki Onishi team's companion robot [5], Companion Robot [6], and OpenBot [15]. We designed a robot capable of tracking elderly when they are alone at home with the ability to move on flat surfaces at a speed equal to that of elderly people. ...
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span lang="EN-US">Recently, elderly population increasing worldwide has put higher pressure on health-care providers and their families. The advent of elderly care robots will reduce that pressure. In this paper, a design of mobile servant robot with integrated tracking algorithm in order to assist the elderly by companionship is proposed not only to help families take care of their elderly at home but also reduce the pressure on health-care providers. The proposed robot is based on humanoid structure and AI-embedded-GPU controller. The design allows the robot to follow the elderly and accompany them in real-time. In addition, the video streaming algorithm with the pipeline mechanism is integrated on robot controllers so that the owner interacts with the elderly through the internet. The robot controller is embedded into hardware of 128 graphics processing unit cores and 4 ARM Cortex-A9 cores in order to execute convolutional neural network (NCNN) algorithms for elderly recognition and body tracking. The processing speed at 14 fps of video stream in real-time. The proposed robot can move on uneven surfaces with a speed at 0.21 m/s and an accuracy over 90%. However, the video stream processing speed is able to be reduced at 15 fps and latency less than 415 ms when four users appear concurrently. </span
... The design of friendly robots to help individuals is a fervent field. Buddy [148] is a highly engaging social robot. Buddy deploys many assets for social interaction such as its appealing design, its anthropomorphic face able to display emotional reactions and its ability to be proactive to look for a user and propose activities. ...
Thesis
The employment of personal robots or service robots has aroused much interest in recent years with an amazing growth of robotics in different domains. Design of companion robots able to assist, to share and to accompany individuals with limited autonomy in their daily life is the challenge of the future decade. However, performances of nowadays robotic bodies and prototypes remain very far from defeating such challenge. Although sophisticated humanoid robots have been developed, much more effort is needed for improving their cognitive capabilities.Actually, the above-mentioned commercially available robots or prototypes are not still able to naturally adapt themselves to the complex environment in which they are supposed to evolve with humans. In the same way, the existing prototypes are not able to interact in a versatile way with their users. In fact they are still very far from interpreting the diversity and the complexity of perceived information or to construct knowledge relating the surrounding environment. The development of bio-inspired approaches based on Artificial Cognition for perception and autonomous acquisition of knowledge in robotics is a feasible strategy to overcome these limitations. A number of advances have already conducted to the realization of an artificial-cognition-based system allowing a robot to learn and create knowledge from observation (association of sensory information and natural semantics). Within this context, the present work takes advantage from evolutionary process for semantic interpretation of sensory information to make emerge the machine-awareness about its surrounding environment. The main purpose of the Doctoral Thesis is to extend the already accomplished efforts (researches) in order to allow a robot to extract, to construct and to conceptualize the knowledge about its surrounding environment. Indeed, the goal of the doctoral research is to generalize the aforementioned concepts for an autonomous, or semi-autonomous, construction of knowledge from the perceived information (e.g. by a robot). In other words, the expected goal of the proposed doctoral research is to allow a robot progressively conceptualize the environment in which it evolves and to share the constructed knowledge with its user. To this end, a semantic-multimedia knowledge base has been created based on an ontological model and implemented through a NoSQL graph database. This knowledge base is the founding element of the thesis work on which multiple approaches have been investigated, based on semantic, multimedia and visual information. The developed approaches combine this information through classic machine learning techniques, both supervised and unsupervised, together with transfer learning techniques for the reuse of semantic features from deep neural networks models. Other techniques based on ontologies and the Semantic Web have been explored for the acquisition and integration of further knowledge in the knowledge base developed. The different areas investigated have been united in a comprehensive logical framework. The experiments conducted have shown an effective correspondence between the interpretations based on semantic and visual features, from which emerged the possibility for a robotic agent to expand its knowledge generalization skills in even unknown or partially known environments, which allowed to achieve the objectives set.
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