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Proper platform pose is important for the mobile manipulator to accomplish dexterous manipulation tasks efficiently and safely, and the evaluation criterion to qualify manipulation performance is critical to support the pose decision process. This paper aims to present a comprehensive index to evaluate the manipulator’s operation performance from various aspects.

In this research, a criterion called hybrid manipulability (HM) is proposed to assess the performance of the manipulator’s operation, considering crucial factors such as joint limits, obstacle avoidance and stability. The determination of the optimal platform pose is achieved by selecting the pose that maximizes the HM within the feasible inverse reachability map associated with the target object.

A self-built mobile manipulator is adopted as the experimental platform, and the feasibility of the proposed method is experimentally verified in the context of object-grasping tasks both in simulation and practice.

The proposed HM extends upon the conventional notion of manipulability by incorporating additional factors, including the manipulator’s joint limits, the obstacle avoidance situation during the operation and the manipulation stability when grasping the target object. The manipulator can achieve enhanced stability during grasping when positioned in the pose determined by the HM.

This conceptual paper aims to explore the possibility of human beings reaching a virtual form of immortality.

The paper is an investigation of the path from an early example of human knowledge to the birth of artificial intelligence (AI) and robots. A critical analysis of different point of views, from philosophers to scientists, is presented.

From ancient rock art paintings to the moon landing, human knowledge has made a huge progress to the point of creating robots resembling human features. While these humanoid robots can successfully undertake risky tasks, they also generate ethical issues for the society they interact with.

The paper is conceptual, and it does attempt to provide one theory by which human beings can achieve the dream of immortality. It is part of a work in progress on the use of AI and the issues related to the creation/use of humanoid robots in society.

This paper provides an overview of some of the key issues and themes impacting our modern society. Its originality resides in the linking of human knowledge to collective knowledge and then of collective mind to the hyper-collective mind. The idea of humans reaching immortality is burdened by the imperative need to define ethical guidelines for the field of AI and its uses.

Social robots are invading our daily lives. Recently, thanks to artificial intelligence, humanoid social robots have been developed and influence individuals on social media. This paper aims to understand the perception of luxury consumers regarding human-like virtual influencers (VI) in a multicultural context.

Conducting a qualitative method, the authors interviewed 32 Chinese and French consumers of luxury products from the Gen-Z and millennial generation about their perception of human influencers and human-like VI after following them on social media specific platforms.

Using source credibility theory, this research unveils the different ways in which consumers perceive human-like VI according to their physical or content attractiveness, expertise, similarities and trustworthiness. The results suggest that the perception of human-like VI by millennials and Gen-Z is closely related to their cultural setting and their familiarity of the technology in a luxury context.

Considering Gen-Z and millennials' willing for para-social interactions and given the importance to the credibility of the source or the emotions displayed by VI, the intercultural empirical setting of this study introduces the ambivalence of the perception of social robots versus human-like influencers in a luxury digital context.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

Robots face fundamental challenges in achieving reliable and stable operations for complex home service scenarios. This is one of the crucial topics of robotics methods to imitate human beings’ advanced cognitive characteristics and apply them to solve complex tasks. The purpose of this study is to enable robots to have the ability to understand the scene and task process in complex scenes and to provide a reference method for robot task programming in complex scenes.

This paper constructs a task modeling method for robots in complex environments based on the characteristics of the perception-motor memory model of human cognition. In the aspect of episodic memory construction, the task execution process is included in the category of qualitative spatio-temporal calculus. The topology interaction of objects in a task scenario is used to define scene attributes. The task process can be regarded as changing scene attributes on a time scale. The qualitative spatio-temporal activity graphs are used to analyze the change process of the object state with time during the robot task execution. The tasks are divided according to the different values of scene attributes at different times during task execution. Based on this, in procedural memory, an object-centered motion model is developed by analyzing the changes in the relationship between objects in the scene episode by analyzing the scene changes before and after the robot performs the actions. Finally, the task execution process of the robot is constructed by alternately reconstructing episodic memory and procedural memory.

To verify the applicability of the proposed model, a scenario where the robot combines the object (one of the most common tasks in-home service) is set up. The proposed method can obtain the landscape of robot tasks in a complex environment.

The robot can achieve high-level task programming through the alternating interpretation of scenarios and actions. The proposed model differs from traditional methods based on geometric or physical feature information. However, it focuses on the spatial relationship of objects, which is more similar to the cognitive mechanism of human understanding of the environment.