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This paper aims to present a new kinematics mapping method based on dynamic equivalent points. In teleoperation, this method enables a robotic (follower) arm to mimic human (leader) arm postures and avoid obstacles in a human-like manner.

The information of the human arm is extracted based on the characteristics of human arm motion, and the concept of equivalent points is introduced. Then, an equivalent point is determined to transform the robotic arm with a nonhuman-like kinematic structure into an anthropomorphic robotic arm. Based on this equivalent point, a mapping method is developed to ensure that the two arms are similar. Finally, the similarity between the human elbow angle and robot elbow angle is further improved by using this method and an augmented Jacobian matrix with a compensation coefficient.

Numerical simulations and physical prototype experiments are conducted to verify the effectiveness and feasibility of the proposed method. In environments with obstacles, this method can adjust the position of the equivalent point in real time to avoid obstacles. In environments without obstacles, the similarity between the human elbow angle and robot elbow angle is further improved at the expense of the end-effector accuracy.

This study presents a new kinematics mapping method, which can realize the complete mapping between the human arm and heterogeneous robotic arm in teleoperation. This method is versatile and can be applied to various mechanical arms with different structures.

The purpose of this paper is to present a novel data glove which can capture the motion of the arm and hand by inertial and magnetic sensors. The proposed data glove is used to provide the information of the gestures and teleoperate the robotic arm-hand.

The data glove comprises 18 low-cost inertial and magnetic measurement units (IMMUs) which not only make up the drawbacks of traditional data glove that only captures the incomplete gesture information but also provide a novel scheme of the robotic arm-hand teleoperation. The IMMUs are compact and small enough to wear on the upper arm, forearm, palm and fingers. The calibration method is proposed to improve the accuracy of measurements of units, and the orientations of each IMMU are estimated by a two-step optimal filter. The kinematic models of the arm, hand and fingers are integrated into the entire system to capture the motion gesture. A positon algorithm is also deduced to compute the positions of fingertips. With the proposed data glove, the robotic arm-hand can be teleoperated by the human arm, palm and fingers, thus establishing a novel robotic arm-hand teleoperation scheme.

Experimental results show that the proposed data glove can accurately and fully capture the fine gesture. Using the proposed data glove as the multiple input device has also proved to be a suitable teleoperating robotic arm-hand system.

Integrated with 18 low-cost and miniature IMMUs, the proposed data glove can give more information of the gesture than existing devices. Meanwhile, the proposed algorithms for motion capture determine the superior results. Furthermore, the accurately captured gestures can efficiently facilitate a novel teleoperation scheme to teleoperate the robotic arm-hand.

The purpose of this paper is to present the control methods of the exoskeleton robotic arm for stroke rehabilitation.

The robotic arm is driven by the pneumatic muscle actuators. The control system provides independent control for the robot. The joint axes of the robotic arm are arranged to mimic the natural upper limb workspace.

Findings are the classification of training modes and control methods of rehabilitation training, and the characters of both the instant spasm and the sustaining one.

This paper is a preliminary step in the control system and the kinematical characteristics should be analyzed to achieve high precision of movement.

Based on a hierarchical structure, the control system allows the execution of sequence of switching control methods: position, force, force/position and impedance. Patient‐active‐robot‐passive and patient‐passive‐robot‐active (PPRA) training modes are also presented in this paper. In PPRA mode, the robotic arm can provide pre‐specified resistances on the patient's arm. Both instant and sustaining spasms are taken into account for safety.

The purpose of this paper is to present a robotic arm that can offer better stiffness than traditional industrial robots for improving the quality of holes in robotic drilling process.

The paper introduces a five-degree of freedom (DOF) robot, which consists of a waist, a big arm, a small arm and a wrist. The robotic wrist is composed of two DOFs of pitching and tilting. A parallelogram frame is used for robotic arms, and the arm is driven by a linear electric cylinder in the diagonal direction. Double screw nuts with preload are used in the ball screw to remove the reverse backlash. In addition, dual-motor drive is applied for each DOF in the waist and the wrist to apply anti-backlash control method for eliminating gear backlash.

The proposed robotic arm has the potential for improving robot stiffness because of its truss structure. The robot can offer better stiffness than industrial robots, which is beneficial to improve the quality of robotic drilling holes.

This paper includes the design of a five-DOF robot for robotic drilling tasks, and the stiffness modeling of the robot is presented and verified by the experiment. The robotic system can be used instead of traditional industrial robots for improving the hole quality to a certain extent.

Robot-assisted system for minimally invasive surgery (MIS) has been attracting more and more attentions. Compared with a traditional MIS, the robot-assisted system for MIS is able to overcome or reduce defects, such as poor hand-eye coordination, heavy labour intensity and limited motion of the instrument. The purpose of this paper is to design a novel robotic system for MIS applications.

A robotic system with three separate slave arms for MIS has been designed. In the proposed robot, a new mechanism was designed as the remote centre motion (RCM) mechanism to restrain the movement of instrument or laparoscope around the incision. Moreover, an improved instrument without coupling motion between wrist and grippers was developed to enhance its manipulability. A control system architecture was also developed, and an intuitive control method was applied to realize hand-eye coordination of the operator.

For the RCM mechanism, the workspace was analyzed and the positioning accuracy of the remote centre point was tested. The results show that the RCM mechanism can be applied to MIS. Furthermore, the master-slave trajectory tracking experiments reveal that slave robots are able to follow the movement of the master manipulators well. Finally, the feasibility of the robot-assisted system for MIS is proved by performing animal experiments successfully.

This paper offers a novel robotic system for MIS. It can accomplish the anticipated results.

Stiffness adjusting ability is essential for soft robotic arms to perform complex tasks. A soft state enables dexterous operation and safe interaction, while a rigid state enables large force output or heavy weight carrying. However, making a compact integration of soft actuators with powerful stiffness adjusting mechanisms is challenging. This study aims to develop a piston-like particle jamming mechanism for enhanced stiffness adjustment of a soft robotic arm.

The arm has two pairs of differential tendons for spatial bending, and a jamming core consists of four jamming units with particles sealed inside braided tubes for stiffness adjustment. The jamming core is pushed and pulled smoothly along the tendons by a piston, which is then driven by a motor and a ball screw mechanism.

The tip displacement of the arm under 150 N jamming force and no more than 0.3 kg load is minimal. The maximum stiffening ratio measured in the experiment under 150 N jamming force is up to 6–25 depends on the bending direction and added load of the arm, which is superior to most of the vacuum powered jamming method.

The proposed robotic arm makes an innovative compact integration of tendon-driven robotic arm and motor-driven piston-like particle jamming mechanism. The jamming force is much larger compared to conventional vacuum-powered systems and results in a superior stiffening ability.

This paper describes the development of the ARM System, an advanced subsea manipulator for weld inspection. ARM uses an advanced man‐machine interface and provides robotic control of the manipulator using techniques developed in factory robots. A more advanced robotic control system, Polecat, is currently being developed using experience gained from ARM and will be used in an ROV pilot trainer, Rovsim, and a number of European and commercial projects ‐ not just subsea but also in nuclear and factory environments.

Supernumerary robotic limbs (SRLs) are a new type of wearable robot, which improve the user’s operating and perceive the user’s environment by extra robotic limbs. There are some literature reviews about the SRLs’ key technology and development trend, but the design of SRLs has not been fully discussed and summarized. This paper aims to focus on the design of SRLs and provides a comprehensive review of the ontological structure design of SRLs.

In this paper, the related literature of SRLs is summarized and analyzed by VOSviewer. The structural features of different types of SRLs are extracted, and then discuss the design approach and characteristics of SRLs which are different from typical wearable robots.

The design concept of SRLs is different from the conventional wearable robots. SRLs have various reconfiguration and installed positions, and it will influence the safety and cooperativeness performance of SRLs.

This paper focuses on discussing the structural design of SRLs by literature review, and this review will help researchers understand the structural features of SRLs and key points of the ontological design of SRLs, which can be used as a reference for designing SRLs.

This paper aims to present a novel lightweight distribution grid operating robot system with focus on lightweight and multi-functionality, aiming for autonomous and live-line maintenance operations.

A ground-up redesign of the dual-arm robotic system with 12-DoF is applied for substantial weight reduction; a dual-mode operating control framework is proposed, with vision-guided autonomous operation embedded with real-time manual teleoperation controlling both manipulators simultaneously; a quick-swap tooling system is developed to conduct multi-functional operation tasks. A prototype robotic system is constructed and validated in a series of operational experiments in an emulated environment both indoors and outdoors.

The overall weight of the system is successfully brought down to under 150 kg, making it suitable for the majority of vehicle-mounted aerial work platforms, and it can be flexibly and quickly deployed in population dense areas with narrow streets. The system equips with two dexterous robotic manipulators and up to six interchangeable tools, and a vision system for AI-based autonomous operations. A quick-change tooling system ensures the robot to change tools on-the-go without human intervention.

The resulting dual-arm robotic live-line operation system robotic system could be compact and lightweight enough to be deployed on a wide range of available aerial working platforms with high mobility and efficiency. The robot could both conduct routine operation tasks fully autonomously without human direct operation and be manually operated when required. The quick-swap tooling system enables lightweight and durable interchangeability of multiple end-effector tools, enabling future expansion of operating capabilities across different tasks and operating scenarios.

In the past decade, more than 700 million people are affected by some kind of disability or handicap. In this context, the research interest in assistive robotics is growing up. For people with mobility impairments, daily life operations, as dressing or feeding, require the assistance of dedicated people; thus, the use of devices providing independent mobility can have a large impact on improving their life quality. The purpose of this paper is to present the development of a robotic system aimed at assisting people with this kind of severe motion disabilities by providing a certain level of autonomy.

The system is based on a hierarchical architecture where, at the top level, the user generates simple and high-level commands by resorting to a graphical user interface operated via a P300-based brain computer interface. These commands are ultimately converted into joint and Cartesian space tasks for the robotic system that are then handled by the robot motion control algorithm resorting to a set-based task priority inverse kinematic strategy. The overall architecture is realized by integrating control and perception software modules developed in the robots and systems environment with the BCI2000 framework, used to operate the brain–computer interfaces (BCI) device.

The effectiveness of the proposed architecture is validated through experiments where a user generates commands, via an Emotiv Epoc+ BCI, to perform assistive tasks that are executed by a Kinova MOVO robot, i.e. an omnidirectional mobile robotic platform equipped with two lightweight seven degrees of freedoms manipulators.

The P300 paradigm has been successfully integrated with a control architecture that allows us to command a complex robotic system to perform daily life operations. The user defines high-level commands via the BCI, letting all the low-level tasks, for example, safety-related tasks, to be handled by the system in a completely autonomous manner.