Interaction Studies - Volume 20, Issue 1, 2019

Social interaction, especially for older people living alone is a challenge currently facing human-robot interaction (HRI). There has been little research on user preference towards HRI interfaces. In this paper, we took both objective observations and participants’ opinions into account in studying older users with a robot partner. The developed dual-modal robot interface offered older users options of speech or touch screen to perform tasks. Fifteen people aged from 70 to 89 years old, participated. We analyzed the spontaneous actions of the participants, including their attentional activities and conversational activities, the temporal characteristics of these social behaviours, as well as questionnaires. It has been revealed that social engagement with the robot demonstrated by older people was no different from what might be expected towards a human partner. This study is an early attempt to reveal the social connections between human beings and a personal robot in real life.

Tactile emotion recognition provides a lot of valuable information in human-computer interaction, and it has strong application prospects in many aspects such as smart home and medical treatment. So this situation raises a question: How to quickly and efficiently let the robot perform the correct emotion recognition? In this work, we develop a lifelong learning algorithm which is based on the efficient dictionary learning technology, to tackle the tactile emotion recognition across different tasks. To verify the efficiency of the proposed method, we applied it to two data sets for experimentation: Corpus of Social Touch (CoST) and our dataset(We built it with a 12X12 array sensor). The results show that the proposed lifelong learning algorithm achieves satisfactory results.

Customized bus services are conducive to improving urban traffic and environment, and have attracted widespread attention. However, the problems encountered in the new customized bus mode include the large difference between the basis of customized bus passenger flow data analysis and the basis of the traditional bus passenger flow data analysis, and the difficulty in different vehicle scheduling caused by the combination of traditional and customized bus modes. We propose a customized bus passenger flow analysis algorithm and multi-destination customized bus line capacity scheduling algorithm, and display them in an intuitive way. The experimental results show that the algorithm model established in this paper can basically meet the data requirements of operation and management, and can provide decision support for customized bus line planning.

“Rough set” is a theory put forward by the polish scholar Z. Pawlak, which is a useful mathematics tool for dealing with vague and uncertain information. Rough set theory can achieve a subset of all attribute which preserves the discernible ability of original features, by using the data only with no additional information. As a typical system of multi-agent, the decision-making system of soccer robot has the features of multi-layered, antagonism, and cooperation. On the bases of rough set theory, this paper established a decision making system with complete information for soccer robot, and then reduce the condition and decision attributes and their values, to get the simply decision rules. On the otherwise, considering the situation of information loss, we study decision making of imperfect information system, extract the decision rules and calculate the reliability, so that the rules can assist the agent to make right decision in competition. The simulation result shows that the algorithm is correct and effective.

The localization and navigation technology are the key factors in the research of mobile robots. With the demand of smart manufacturing industry and the development of robotics technology, the importance of mobile robot has become increasingly prominent. Mobile robot positioning research is mostly based on odometry, however, it has cumulative errors that would affect the accuracy of positioning results.

This paper describes an improved measurement model that suitable from 0° to 180° and used this model in the Extended Kalman Filter (EKF) and Unscented Kalman Filter(UKF) time update step respectively, the method can address the interference of kinematics model predicted position and heading angle, both of them are easily disturbed by noises and other factors. Designing a tracked mobile robot as experimental platform to collect the raw data, conducting experimental research including the performance of hardware platform and autonomous obstacle avoidance, the real-time and stability of remote data interaction, and the accuracy of optimal pose estimation. The simulation results have been verified the accuracy of the improved measurement model applied to UKF.

Human-robot collaboration, whereby the human and the robot join their forces to achieve a task, opens new application opportunities in manufacturing. Robots can perform precise and repetitive operations while humans can execute tasks that require dexterity and problem-solving abilities. Moreover, collaborative robots can take over heavy-duty tasks. Musculoskeletal disorders (MSDs) are a serious health concern and the primary cause of absenteeism at work. While the role of the human is still essential in flexible production environment, the robot can help decreasing the workload of workers. This paper describes a novel framework for task allocation of human-robot assembly applications based on capabilities and ergonomics considerations. Capable agents are determined on the basis of agent characteristics and task requirements. Ergonomics is integrated by measuring the human body posture and the related workload. The developed framework was validated on a gearbox assembly use case using the collaborative robot Baxter.

Robot is definitely playing important role in human society. Low contact on machine standards is mostly on industrial robot while close contacts are in increasing demand in service robot, etc. The development of robotics with advanced hardware and artificial intelligence (AI) provide the possibility with human beings while close contacts raise many new issues on ethics and risks. For interaction, the related technique of perception, cognition and interaction are briefly introduced. For ethics, rules should be given for the robot designers to include ethics for certain application while risks should be evaluated during the experiment test. To make efficient decision, safety design with AI technology should be put on agenda for roboticists. Except from the risks, ethics raise many challenges while most of them can be solved by developing technologies while some of the problems exist in human’s society which also raise the questions for the human beings. More broader vision should be taken from different social departments together to avoid the possible embarrassed issues. It’s time to welcome the world of robotics and related techniques will make life more efficient while human-robot coexistence society will come one day and law should be imposed on both.

This paper presents a human-robot closely collaborative solution to cooperatively perform surface treatment tasks such as polishing, grinding, finishing, deburring, etc. The proposed scheme is based on task priority and non-conventional sliding mode control. Furthermore, the proposal includes two force sensors attached to the manipulator end-effector and tool: one sensor is used to properly accomplish the surface treatment task, while the second one is used by the operator to guide the robot tool. The applicability and feasibility of the proposed collaborative solution for robotic surface treatment are substantiated by experimental results using a redundant 7R manipulator: the Sawyer collaborative robot.

A decentralized adaptive control based on human linguistic is investigated to learn human behaviors for multiple robotic manipulators. Many experts’ words or sentences can be transferred into the control actions by employing membership functions in robot systems, which can be synthesized fuzzy controller by employing reasoning mechanism. For the unknown model dynamical robot manipulators, one adjustable parameter that relates to the approximation accuracy of fuzzy logic systems is introduced at first, which be utilized to deal with the unknown dynamics of robot manipulators. Switching fuzzy adaptive controller is designed to overcome the limitation of logic structure that the number of adaptive laws only focus on fuzzy rules in conventional fuzzy logic systems. Another advantage of this design method is that the control with human linguistic extend the semi-global stability to global stability. Finally, effectiveness of the developed control design scheme has been shown in simulation example.