Target Positioning and Grasping of NAO Robot Based on Monocular Stereo Vision

With the continuous advancement of science and technology and the rapid development of robotics, it has become an inevitable trend for domestic robots to enter thousands of households. In order to solve the inconvenience problem of the elderly and people with special needs, because the elderly and other people in need may need the help of domestic robots due to inconvenient legs and feet, the research of the robot target position based on monocular stereo vision and the understanding of the robot NAO are very important. Research and experiments are carried out on the target recognition and positioning in the process of NAO robot grasping. This paper proposes a recognition algorithm corresponding to quantitative component statistical information. First, extract the area of interest that contains the purpose from the image. After that, to eliminate interference in various fields and achieve target recognition, the robot cameras have almost no common field of view and can only use one camera at the same time. Therefore, this article uses the monocular vision principle to locate the target, and the detection algorithm is based on the structure of the robot head material, establishes the relationship between the height change of the machine head and the tilt angle, and improves the monocular vision NAO robot detection algorithm. According to experiments, the accuracy of the robot at close range can be controlled below 1 cm. This article completes the robot’s grasping and transmission of the target. About 80% of the external information that humans can perceive comes from vision. In addition, there are advantages such as high efficiency and good stability.

Exploring Social and Assistive Domestic Robots for Older Adults: Robot Sociability, Trust, and Acceptance

Older adults prefer to age in place, to live independently while maintaining social connection and engagement with the community. Though older adults can encounter barriers to these goals, social and assistive domestic robots hold promise for promoting independence and online/offline social engagement. However, social robots must be designed to meet their needs and preferences. Open questions remain regarding how to facilitate the development of trust and acceptance in robot support. We investigated the associations between robot social characteristics, sociability, trust, and acceptance for instrumental activities of daily living. We used an online survey to assess older adults’ perceptions towards social and assistive robots. Robots with more social abilities were rated as more acceptable and trustworthy across different task types. We discuss design implications that may promote the development of robot trust and acceptance by older adults, and ultimately help enable aging in place and social engagement.

On the Gap between Domestic Robotic Applications and Computational Intelligence

Aspired to build intelligent agents that can assist humans in daily life, researchers and engineers, both from academia and industry, have kept advancing the state-of-the-art in domestic robotics. With the rapid advancement of both hardware (e.g., high performance computing, smaller and cheaper sensors) and software (e.g., deep learning techniques and computational intelligence technologies), robotic products have become available to ordinary household users. For instance, domestic robots have assisted humans in various daily life scenarios to provide: (1) physical assistance such as floor vacuuming; (2) social assistance such as chatting; and (3) education and cognitive assistance such as offering partnerships. Crucial to the success of domestic robots is their ability to understand and carry out designated tasks from human users via natural and intuitive human-like interactions, because ordinary users usually have no expertise in robotics. To investigate whether and to what extent existing domestic robots can participate in intuitive and natural interactions, we survey existing domestic robots in terms of their interaction ability, and discuss the state-of-the-art research on multi-modal human–machine interaction from various domains, including natural language processing and multi-modal dialogue systems. We relate domestic robot application scenarios with state-of-the-art computational techniques of human–machine interaction, and discuss promising future directions towards building more reliable, capable and human-like domestic robots.

Reliable CPS Design for Unreliable Hardware Platforms

Today, many battery-operated cyber-physical systems (CPS) ranging from domestic robots, to drones, and electric vehicles are highly software-intensive. The software in such systems involves multiple feedback control loops that implement different functionality. How these control loops are designed is closely related to both the semiconductor aging of the processors on which the software is run and also the aging of the batteries in these systems. For example, sudden acceleration in an electric vehicle can negatively impact the health of the vehicle’s battery. On the other hand, processors age over time and stress, impacting the execution of control algorithms and thus the control performance. With increasing semiconductor scaling, and our increasing reliance on battery-operated devices, these aging effects are of concern for the lifetime of these devices. Traditionally, the design of the control loops focused only on control-theoretic metrics, related to stability and performance (such as peak overshoot or settling time). In this chapter we show that such controller design techniques that are oblivious of the characteristics of the hardware implementation platform dramatically worsen the battery behaviour and violate the safety requirement with processor aging. However, with proper controller design these effects can be mitigated—thereby improving the lifetime of the devices.

Retracted: Artificial Intelligence Relationship on Consumer Behavior in Marketing Theory

Various recently-introduced applications of artificial intelligence (AI) operate at the interface between businesses and consumers. This paper looks at whether these innovations have relevant implications for marketing theory. The latest literature on the connection between AI and marketing has emphasized a great variety of AI applications that qualify this relationship. Based on these studies but focusing only on the applications with a direct impact on the relationship at the very heart of marketing, i.e., the one between firms and consumers, the paper analyzes three categories of AI applications: AI-based shipping-then-shopping, AI-based service robots, and AI-based smart products and domestic robots. The main result of this first analysis is that all three categories have to do, each in their own way, with mass customization. A discussion of this common trait leads us to recognize their ways to mass customization that – unlike the traditional approach developed thanks to flexible automation and product modularity technologies – place the customization process within a broader perspective of consumer needs management. This change in approach means that marketing should focus more on managing consumers’ needs than directly on the satisfaction of those needs. This finding marks a genuine discontinuity that opens up a new space for reflection for scholars and marketing managers alike. Retraction Notice: This paper has been retracted from the journal after receipt of written complains. This journal is determined to promote integrity in research publication. This retraction is in spirit of the same. After formal procedures editor(s) and publisher have retracted this paper on 10th November-2020. Related policy is available here: http://goo.gl/lI77Nn

How artificial intelligence can change the core of marketing theory

Various recently-introduced applications of artificial intelligence (AI) operate at the interface between businesses and consumers. This paper looks at whether these innovations have relevant implications for marketing theory. The latest literature on the connection between AI and marketing has emphasized a great variety of AI applications that qualify this relationship. Based on these studies but focusing only on the applications with a direct impact on the relationship at the very heart of marketing, i.e., the one between firms and consumers, the paper analyzes three categories of AI applications: AI-based shipping-then-shopping, AI-based service robots, and AI-based smart products and domestic robots. The main result of this first analysis is that all three categories have to do, each in their own way, with mass customization. A discussion of this common trait leads us to recognize their ways to mass customization that – unlike the traditional approach developed thanks to flexible automation and product modularity technologies – place the customization process within a broader perspective of consumer needs management. This change in approach means that marketing should focus more on managing consumers’ needs than directly on the satisfaction of those needs. This finding marks a genuine discontinuity that opens up a new space for reflection for scholars and marketing managers alike.