关键词： Unmeasurable angular velocity   Bounded disturbances   Subsystems   Adaptive robust finite-time control   Bioinspired neurodynamics method   Lyapunov-Krasovskii functional  

摘要： This paper addresses the adaptive robust finite-time bioinspired neurodynamics control (ARFBNC) for a class of mobile robots with unmeasurable angular velocity and multiple time-varying bounded disturbances. The error system of the mobile robot is decomposed into two subsystems based on the system model. The state feedback control laws with disturbance feed-forward compensators are designed for the two subsystems, respectively. The ARFBNC method is designed based on the state feedback control laws and two subsystems. The stability conditions in the form of linear matrix inequalities (LMIs) are derived by introducing the Lyapunov-Krasovskii functional. Unlike other works, both the unmeasurable angular velocity and multiple time-varying bounded disturbances are estimated effectively. The smooth bounded outputs are obtained and the sharp jumps of initial values for the state errors are reduced. By introducing the Lyapunov-Krasovskii functional, the closed-loop system is asymptotically stable and the state errors converge to an adjustable bounded region. Finally, three examples are given to show the effectiveness and advantage of the proposed methods.

摘要： Presents the President’s message for this issue of the publication.

关键词： Redundant dual-arm robot   Learning from demonstration   Human-arm coordination constraint  

摘要： The motion of a redundant dual-arm robot is subject to dual-arm coordination constraints when performing a coordination task. However, these constraints are usually fixed. To improve the ability of dual arm robots to interact effectively with human beings, it is necessary to obtain the variable dual-arm coordination constraints from the observation of human arm motion. This paper developed a novel redundant dual-arm robot motion learning method based on human-arm coordination characteristics. It can realize the human-like coordination motion of a dual-arm robot in both Cartesian space and joint space. The proposed method was implemented on a real redundant dual-arm robot platform. Experiments involving two tasks, carrying and pouring, were carried out, and the results indicate that the robot can successfully reproduce the demonstrated human-arm motion tasks, and the dual-arm robot has the characteristics of coordinated human-like motion, making robotic dual-arm manipulations more smooth and natural.

关键词： Human-robot interaction   Robotics   Children with autism  

摘要： Robotics research in helping children with autism has gained increased attention in recent years. Children with autism often struggle with neurodevelopmental disorders that affect their lives particularly in communication skills, social interaction and their repetitive stereotyped behavior. In this article, we highlight previous findings on human-robot interaction for children with autism. To date, it has been claimed that child-robot interaction is a beneficial approach in helping children with autism to improve their quality of life. Based on an extensive search of the literature, we identified three major research gaps: (1) diversity in research focus, (2) bias contribution in robotics research towards specific behavior impairments in autism and, (3) effectiveness of human-robot interaction after robot-based intervention program. Therefore, this review paper shall identify and thoroughly discuss published works that address the research gaps found in this areas. This article is therefore seen as a crucial step in bridging the gap between robotics research and children with autism. The results presented could be beneficial for researchers in determining future directions for robotics research in helping children with autism.

关键词： Adaptive control   mobile robot   trajectory-tracking control   tube-based model predictive control (MPC)  

摘要： This paper addresses a trajectory-tracking control problem for mobile robots by combining tube-based model predictive control (MPC) in handling kinematic constraints and adaptive control in handling dynamic constraints. In order to handle kinematic constraints, the tube-based MPC scheme is introduced, which includes the state feedback controller to suppress the external disturbance in the velocity level. The tube-based MPC is transformed to a constrained quadratic programming (QP) problem, and then the QP problem can be efficiently solved by a primal-dual neural network over a finite receding horizon so as to obtain the optimal control velocity. Besides, an adaptive controller employing the neural network technology is proposed to acquire the approximation of the uncertain robotic dynamics. Moreover, an auxiliary control is developed in order to deal with actuator saturation, and a disturbance observer is designed to reject the external disturbance online in the dynamic level. Subsequently, through Lyapunov function synthesis, the stability of the closed-loop system have been guaranteed. Finally, in order to verify the effectiveness, the experimental studies are carried out using an actual mobile robot.

关键词： Educational robotics   Inclusive education   Special needs   Socio-economic status   Cultural diversity   Gender differences  

摘要： It has been quite a long time since S. Papert introduced the idea that children should be involved in the use of computers in the learning process to support the development of computational thinking. Nowadays, educational robotics is introduced in different dimensions of education, but mostly it is used as part of a compulsory educational process in nonformal educational activities, in activities to reduce the risks of early school leaving, and in initiatives introduced by some projects where different aspects of educational robotics are tested in activities with students who have diverse special needs. But till now robotics has mostly been associated with the field of Science, Technology, Engineering, and Mathematics, and outcomes of educational robotics are measured through the prism of improved knowledge in STEM subjects. In this special issue, journal researchers provide results on ER in the context of inclusive education.

关键词： Autonomy   AUV   lithium-ion   navigation   optical   swarm  

摘要： Reliable power supply, precise position determination and effective communication are the key requirements for strategic autonomous underwater vehicles (AUV) involved in long duration scientific missions, search operations and when operated as a swarm. The paper presents the challenging range of AUV developed for deep water, Polar and intervention applications;demanding technical requirements for strategic AUV;reliability modeling done on the lithium-ion batteries to identify the redundancy requirements for achieving near-zero failures;navigation model to estimate the achievable level of position accuracies using the state-of-the-art navigation system;limitations in underwater communication;and their importance in realizing vehicle autonomy and swarm intelligence. It is identified that a strategic grade Doppler velocity- aided inertial navigation system could provide position accuracies of about 0.5% of the distance travelled when navigated using sea bottom or ice reference, and a 38 kWh lithium-ion battery pack requires about 7% redundant battery capacity to achieve a failure probability of < 1% in a period of 1 year.

关键词： Artificial intelligence   Education   Healthcare robots   Robot design   Robotics   Humanoid robots  

摘要： Purpose The following paper is a "Q&A interview" conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry PhD and innovator regarding her pioneering efforts and the challenges of bringing a technological invention to market. This paper aims to discuss these issues. Design/methodology/approach The interviewee is Dr Maja Mataric, Chan Soon-Shiong Distinguished Professor in the Computer Science Department, Neuroscience Program, and the Department of Pediatrics at the University of Southern California, founding director of the USC Robotics and Autonomous Systems Center (RASC), co-director of the USC Robotics Research Lab and Vice Dean for Research in the USC Viterbi School of Engineering. In this interview, Mataric shares her personal and business perspectives on socially assistive robotics. Findings Mataric received her PhD in Computer Science and Artificial Intelligence from MIT in 1994, MS in Computer Science from MIT in 1990 and BS in Computer Science from the University of Kansas in 1987. Inspired by the vast potential for affordable human-centered technologies, she went on to found and direct the Interaction Lab, initially at Brandeis University and then at the University of Southern California. Her lab works on developing human-robot non-physical interaction algorithms for supporting desirable behavior change;she has worked with a variety of beneficiary user populations, including children with autism, elderly with Alzheimer's, stroke survivors and teens at risk for Type 2 diabetes, among others. Originality/value Mataric is a pioneer of the field of socially assistive robotics (SAR) with the goal of improving user health and wellness, communication, learning and autonomy. SAR uses interdisciplinary methods from computer science and engineering as well as cognitive science, social science and human studies evaluation, to endow robots with the ability