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The workspace mapping method for master-slave isomeric robots is a key research direction. In order to enhance the safety and stability of the operation of such robots, a position-joint hybrid mapping method based on edge drifting is proposed in this paper. First, teleoperation is divided into two phases, that is, task approach and task operation. During the task approach, the edge drifting algorithm is adopted to largely cover the workspace of a robot. Rate mapping is used to quickly control the movement of the slave robot to the target position. During task operation, a hybrid mapping algorithm integrating the Cartesian space and the joint space highly precisely maps both the position and pose of the slave robot to accurately follow the control command of the master end and achieve precise control. Lastly, the proposed method is validated on the experimental platform for master-slave isomeric teleoperation. The experimental results indicate that this mapping method allows the master-slave isomeric teleoperation system to cover a large workspace precisely with desirable precision in position and pose following.

This article proposes two-terminal sliding mode Control (TSMC) algorithms to simultaneously carry out the disadvantages of variable-time communication delay, finite-time problem and actuator saturation for bilateral teleoperators (BTs). In existing approaches, TSMC laws are achieved by exponential sliding surface enforcing an inequality estimation of time derivative of Lyapunov function. Traditional TSMC schemes are appropriate for considering finite-time convergence. However, they are not able to handle the disadvantage of variable-time communication delay and actuator saturation. To overcome this challenge, we propose two novel TSMC schemes, which allow us to deal with time-varying delays and input constraint. This is achieved by adding the time derivative of errors between two sides and the dynamic term, which is obtained from the deviation between the actual Control input and the computed Control signal. The theoretical analyses are considered by a Lyapunov function candidate using the integral with variable-time delay-based terminals. Our simulation results exhibit the tracking performance under the effect of actuator saturation and variable-time communication delay.

Bilateral teleoperation robots with force feedback enable humans to accomplish these tasks without exposing them to these hazardous environments. Its stability and transparency describe the performance of bilateral teleoperation systems with force feedback. Bilateral teleoperation with force feedback enables humans to combine tactics with optesthesia. However, the force feedback may lead to bilateral teleoperation instability if the communication channels’ time delay exists. The instability of bilateral teleoperation with force feedback, which is brought in by the time delay, has become one of the complicated problems researchers need to solve. Transparency is one of the leading design objectives of the teleoperation system. There are two evaluation criteria for transparency: the accuracy of the position followed by the master mechanical arm and the accuracy of the feedback received by the slave arm from the master arm. The main content of this paper is as follows: 1) This paper researches and summarizes the control structures and control algorithms of several well-developed force-feedback bilateral teleoperation systems and decides to improve the PBTDPA algorithm, which aligns with practical application requirements. 2) The four-channel structure makes the transparency of force-feedback bilateral teleoperation systems perfect in theory. This paper uses the four-channel structure combined with the PBTDPA algorithm to improve the transparency of the approach. 3) Moreover, the delay predictor is used to improve the four-channel power-based time domain passivity approach (PBTDPA) control strategy. The delay differential predictor is added to the communication channel. The delay change rate differential predictor can estimate the communication channel’s delay change rate instead of the maximum delay change rate to improve transparency. The simulation experiment of the improved control strategy was carried out. The results show the excellent performance of our design.

This paper presents the design and implementation of a teleoperation system for a biped wall-climbing robot. A comprehensive kinematic model is developed to support two control modes: position–position (PP) and position–velocity (PV). The control diagram integrates the human operator’s input with real-time feedback from the climbing robot, enabling remote motion control and environmental interaction. A teleoperation device is employed to realize the robot’s motion control. Additionally, the system utilizes markers for visual localization and remote target acquisition, facilitating semi-autonomous navigation during teleoperation. Experimental results demonstrate that the proposed teleoperation system accurately reproduces the intended climbing motions and effectively supports user-guided wall traversal, validating the designed control strategies.

In space teleoperation systems, the dynamics of controlled robots exhibit uncertainties, and communication involves time delays. To address these challenges, this paper proposes a bilateral controller based on a two-layer architecture: the master side employs a radial basis function (RBF) neural network-based sliding mode control, while the slave side uses a model-compensated PD control. The study investigates the teleoperation of a two-degree-of-freedom space robot under fixed time delay conditions. Independent communication channels connect each layer of the master and slave sides, allowing the separation of energy exchange information and control action information. The effectiveness of the proposed teleoperation control system is verified through simulations.

Telekinesis, as commonly portrayed in science fiction literature and cinema, is a super power wherein users control and manipulate objects absent in physical interaction. In real world, enhancing human–robot interaction needs the synthesis of human intuitive processes with robotic arm. This paper introduces a robotic teleoperation system achieving the essence of telekinetic operations, combining the profound capabilities of augmented reality (AR) with the robotic arm operations. Utilizing AR, the proposed methodology offers operators with a visual feedback, facilitating a level of control surpassing the capacities of natural interfaces. By using AR-driven visual recognition, this system achieves operations in a virtual environment, subsequently actualized in the real world through the robotic arm. Through multiple experiments, we found that the system has a small margin of error in telekinesis operations, meeting the needs of remote operation. Furthermore, our system can operate on objects in the real world. These experiments underscore the capability of the remote control system to assist humans in accomplishing a wider range of tasks through the integration of AR and robotic arms, providing a natural human–robot interaction approach.

This volume compiles the peer-reviewed papers presented at the 2nd International Conference on Intelligent Systems and Robotics (CISR 2025), held in Dalian, China, from July 11 to 13, 2025. The symposium served as a vital platform for researchers, engineers, and industry professionals to exchange cutting-edge insights and practical advancements in the rapidly evolving domains of intelligent systems and robotics. Several papers were selected for inclusion in these proceedings and presentation at the symposium, reflecting the vibrant research activity in these fields.The technical program was anchored by four distinguished keynote lectures addressing significant contemporary challenges in cutting-edge research domains. Prof. Chenguang Yang from the University of Liverpool, China, presented groundbreaking work on robot control, learning, perception, and teleoperation systems. Prof. Guangjie Han of Hohai University, China, explored how software is redefining underwater multi-agent networks through innovative architectures, key technologies, and practical applications. Prof. Dayi Wang from the Beijing Institute of Spacecraft System Engineering, China, shared advances in sequential-image autonomous navigation technology based on quantitative characterization of observability. Rounding out this exceptional lineup, Prof. Xuguang Lan from Xi'an Jiaotong University, China, examined the challenges and boundaries of embodied intelligence, with a particular focus on physical world modeling and causal inference. Together, these lectures provided profound insights into some of the most pressing technological questions of our time.We are profoundly grateful to all those who contributed to the remarkable success of CISR 2025. Our sincere appreciation goes to the authors for their insightful research contributions, the reviewers for their diligent evaluations that ensuredacademic rigor, and all attendees whose active participation enriched the conference dialogue. We are especially thankful to our distinguished keynote speakers for delivering thought-provoking presentations that elevated the technical discourse, and to our guest editors, Prof. Xianping Fu from Dalian Maritime University and Prof. Xiaofeng Liu from Hohai University, for their invaluable contributions to shaping the conference's academic content and proceedings. Finally, we gratefully acknowledge the generous sponsorship from Xi'an University of Architecture and Technology, as well as the co-sponsorship from the School of Computer Science and Technology at Dalian Maritime University, Taiyuan University of Technology, and North University of China.List of Conference Organization is available in this PDF.

Robot teleoperation systems face a common set of challenges including latency, low-dimensional user commands, and asymmetric control inputs. User control with Brain–Computer Interfaces (BCIs) exacerbates these problems through especially noisy and erratic low-dimensional motion commands due to the difficulty in decoding neural activity. We introduce a general framework to address these challenges through a combination of computer vision, user intent inference, and arbitration between the human input and autonomous control schemes. Adjustable levels of assistance allow the system to balance the operators capabilities and their perception of control authority. Additionally, a custom servo controller design allow for safe interactions of the robotic arm with the environment. We present experimental results demonstrating significant performance improvement using our shared-control assistance framework on adapted rehabilitation benchmarks with two subjects at various timepoints relative to their implantation with intracortical BCIs. Our results indicate that shared assistance mitigates perceived user difficulty in using a seven-degree of freedom robotic arm as a prosthetic and enables successful performance on previously infeasible tasks. We showcase the extensibility of our architecture with applications to quality-of-life tasks such as opening a door, pouring liquids from containers, and manipulation with objects previously unknown to the system in densely cluttered environments.

Force feedback bilateral teleoperation represents a pivotal advancement in control technology, finding widespread application in hazardous material transportation, perilous environments, space and deep-sea exploration, and healthcare domains. This paper traces the evolutionary trajectory of force feedback bilateral teleoperation from its conceptual inception to its current complexity. It elucidates the fundamental principles underpinning interaction forces and tactile exchanges, with a specific emphasis on the crucial role of tactile devices. In this review, a quantitative analysis of force feedback bilateral teleoperation development trends from 2011 to 2024 has been conducted, utilizing published journal article data as the primary source of information. The review accentuates classical control frameworks and algorithms, while also delving into existing research advancements and prospective breakthrough directions. Moreover, it explores specific practical scenarios ranging from intricate surgeries to hazardous environment exploration, underscoring the technology’s potential to revolutionize industries by augmenting human manipulation of remote systems. This underscores the pivotal role of force feedback bilateral teleoperation as a transformative human-machine interface, capable of shaping flexible control strategies and addressing technological bottlenecks. Future research endeavors in force feedback bilateral teleoperation are expected to prioritize the creation of more immersive experiences, overcoming technical hurdles, fortifying human-machine collaboration, and broadening application domains, particularly within the realms of medical intervention and hazardous environments. With the continuous progression of technology, the integration of human intelligence and robotic capabilities is expected to produce more innovations and breakthroughs in the field of automatic control.

In practice, the time-varying communication delays and actuator failures are the main inevitable issues in nonlinear multilateral teleoperation systems, which can reduce the performance and stability of the considered systems. This article proposed a novel failure-distribution-dependent H∞ fuzzy fault-tolerant control scheme to realize position synchronization and force tracking simultaneously for multilateral teleoperation systems. Firstly, the nonlinear multilateral systems were modeled as a kind of T-S fuzzy systems with multiple time-varying delays. Then, based on the distribution characteristic of failures, by introducing a series of tradeoff coefficients, a novel failure-distribution-dependent fault-tolerant control algorithm was provided to ensure force tracking in spite of failures, and the purpose of position synchronization was achieved (not only the master and slave robot position synchronization but also the position synchronization between each slave robot). Finally, a numerical simulation example was given to show the effectiveness of the proposed method.