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The aim of this article is to provide details of recent technological developments in robotic teleoperation.

Following a short introduction, the two main sections of this article provide examples of recent research involving the application of virtual reality and haptic technologies, respectively, to robotic teleoperation. Brief conclusions are drawn.

Teleoperation systems are being developed which incorporate virtual reality and haptic feedback technologies. Those using virtual reality seek to enhance the operator’s feeling of immersion in the scene and improve their situation awareness and trials involving diverse tasks illustrate that the technology can achieve these aims and overcome many limitations of traditional systems. Haptic feedback further enhances the degree of operator involvement and control and is now being adopted in commercial minimally invasive surgical systems. Systems which combine virtual reality with haptic feedback are being developed and have the potential to allow operators to conduct increasingly complex tasks.

Through reference to recent research, this illustrates how virtual reality and haptic technologies are enhancing the capabilities of robotic teleoperation.

This paper aims to provide insights into the potential of digital technologies-based innovations for more inclusive healthcare by alleviating the affordability, accessibility and availability barriers to utilization of healthcare services. Also, it aims to provide insights into the potential of digital technologies-based innovations for more inclusive services, broadly.

A conceptual framework is inductively developed by analyzing real-world examples of digital technologies-based innovations for more inclusive healthcare through the lenses of economics of information in digital form and certain characteristics of services.

Concurrent implementation of digital technologies-based healthcare innovations with innovations and/or modifications in service processes can enable greater inclusivity by alleviating the affordability, accessibility and availability barriers to utilization of healthcare services.

Issues relating to inequities in healthcare, as a social problem, are the focus of research at multiple levels (e.g. global, national, regional and local) in several academic disciplines. In relation to the scope of the problems and challenges pertaining to providing quality healthcare to the unserved and underserved segments of society, worldwide, the contribution of the proposed framework to practice is modest. However, by highlighting the promise and potential of digital technologies-based innovations as solutions for alleviating barriers to affordability, accessibility and availability of healthcare services during various stages (prevention, detection, diagnosis, treatment and post-treatment follow-up) with illustrative vignettes and developing a framework, the article offers insights for future research. For instance, in reference to mission-driven social enterprises that operate in the product-market space for inclusive innovations under resource constraints, a resourcefulness-based view of the social enterprise constitutes a potential avenue for theory development and research.

Given the conceptual nature of the article, the implications for practice are limited to cognitive implications. Action implications (instrumental implications or implications for practice) are outside of the scope of the article.

Innovations that are economically viable, environmentally sustainable and socially impactful is one of the important issues of our times.

The proposed framework provides insights into the potential of digital technologies-based innovations for more inclusive healthcare by alleviating the affordability, accessibility and availability barriers in the context of emerging and less developed country markets and base of the pyramid segments of society in these markets.

Medical disruptive innovation is essential for deepening the reform of health-care system. The theory of general disruptive innovation assumes that innovations can diffuse by benefiting and attracting consumers through observed and objective relative advantages. Yet decision-makers for adoption in health-care settings are safety-sensitive professionals whose cognitions barriers about underperformance in focal attributes will impede further evaluation of innovation's ancillary performance. Existing studies do not answer the question of how such innovations can overcome safety barriers, find early adopters and grow to the early majority. The purpose of this study is to investigate the process, mechanism, and path of early diffusion of medical disruptive innovation.

The authors conduct a longitudinal case study of the diffusion of Enhanced Recovery After Surgery (ERAS) in China during 2011–2018.

The authors find that the diffusion process of medical disruptive innovations can be viewed as a cognitive evolutionary process that sequentially establishes conformity, differentiation and normalization. Cognition reframing of expert, meaning and benefit for professionals is its implicit mechanism. When adoption may trigger cognitive concerns, actors’ very early (dis)adoption is driven by a combination of structural position, innovation attributes and performance perceptions; central actors then play amplifier roles in the development from early adopters to the early majority.

This study proposes a process theoretical framework for the early diffusion of disruptive innovation. By dissecting the key processes and mechanisms from a cognitive perspective, the study offers theoretical contributions and practical insights into the diffusion of disruptive innovation in professional settings.

Visual feedback control is a promising solution for robots work in unstructured environments, and this is accomplished by estimation of the time derivative relationship between the image features and the robot moving. While some of the drawbacks associated with most visual servoing (VS) approaches include the vision–motor mapping computation and the robots’ dynamic performance, the problem of designing optimal and more effective VS systems still remains challenging. Thus, the purpose of this paper is to propose and evaluate the VS method for robots in an unstructured environment.

This paper presents a new model-free VS control of a robotic manipulator, for which an adaptive estimator aid by network learning is proposed using online estimation of the vision–motor mapping relationship in an environment without the knowledge of statistical noise. Based on the adaptive estimator, a model-free VS schema was constructed by introducing an active disturbance rejection control (ADRC). In our schema, the VS system was designed independently of the robot kinematic model.

The various simulations and experiments were conducted to verify the proposed approach by using an eye-in-hand robot manipulator without calibration and vision depth information, which can improve the autonomous maneuverability of the robot and also allow the robot to adapt its motion according to the image feature changes in real time. In the current method, the image feature trajectory was stable in the camera field range, and the robot’s end motion trajectory did not exhibit shock retreat. The results showed that the steady-state errors of image features was within 19.74 pixels, the robot positioning was stable within 1.53 mm and 0.0373 rad and the convergence rate of the control system was less than 7.21 s in real grasping tasks.

Compared with traditional Kalman filtering for image-based VS and position-based VS methods, this paper adopts the model-free VS method based on the adaptive mapping estimator combination with the ADRC controller, which is effective for improving the dynamic performance of robot systems. The proposed model-free VS schema is suitable for robots’ grasping manipulation in unstructured environments.

The null-space projection method is commonly adopted for controlling redundant robots, which undoubtedly requires the robot Jacobian matrix inverse. This paper aims to provide a novel control scheme, which enables null-space control of redundant robots without conflict with the main task space.

In this paper, an impedance-based null-space control approach for redundant robots is proposed. The null-space degrees of freedom are separated from the primary task space by using the eigenvalue decomposition. Then, a joint impedance controller spans the null space and is reflected into the joint space to manage the redundancy. Finally, several experiments have been conducted to evaluate and validate the performance of the proposed approach in comparison with the null-space projection method under various situations.

Experiment results show that no significant differences were observed between the different filling eigenvalues in the proposed approach under different null-space dimensions and motion velocity. Besides, comparative experiment results demonstrate that the proposed method can achieve comparable results to the null-space projection method. Nevertheless, the suggested approach has benefits regarding the quantity of control parameters in addition to not requiring a Jacobian inverse. Notably, the performance of the proposed method will improve as the null-space dimension increases.

This study presents a new control method for redundant robots, which has advantages for dealing with the problems of controlling redundant robots compared to the existing methods.