In the real practice of multi-AUV (Autonomous Underwater Vehicle) cooperative systems, tasks or malfunctions will change the topology. The process of mutative topology structure will affect the reliability of multi-AUV cooperative system. The interactive Markov chains model, which is an intercurrent model of functional action and capability index, is selected to reflect the reliability of topology-changed multi-AUV cooperative systems. In this model, multi-AUV cooperative systems are described by the conception—“Action”. The concept of “action transfer” is used to describe the topology-changed multi-AUV cooperative system, and model checking is used to solve the interactive Markov chains, giving the probability of reliability within a certain time for the system. The result shows that the method proposed in this paper has a practical value.

This paper presents a new cooperative object transportation technique using parallel line formation with a circular shift. Typical areas of research in relation to object transportation are grasping, pushing, and caging techniques, but these require precise grasping behaviors, iterative motion correction according to the object pose, and the real-time acquisition of the object shape, respectively. In this paper, the proposed technique does not need to consider the shape or the pose of objects, and equipped tools are not necessary for object transportation because objects are transported by pushing behavior only. Multiple robots create parallel line formation using a virtual electric dipole field and then push multiple objects into the formation. This parallel line is extended to the goal using cyclic motion by the robots and the objects are transported to the goal by pushing behavior. The above processes are decentralized and activated based on the finite state machine of each robot. Simulations and practical experiments are presented to verify the proposed technique.

Although image-based visual servoing (IBVS) provides good performance in many dual-arm manipulation applications, it reveals some fatal limitations when dealing with a large position and orientation uncertainty. The object features may leave the camera's field of view, and the dual-arm robot may not converge to their goal configurations. In this paper, a novel vision-based control strategy is presented to resolve these limitations. A visual path planning method for dual-arm end-effector features is proposed to regulate the large initial poses to the pre-alignment poses. Then, the visual constraints between the position and orientation of two objects are established, and the sequenced subtasks are performed to attain the pose alignment of two objects by using a multi-tasks IBVS method. The proposed strategy has been implemented on a MOTOMAN robot to perform the alignment tasks of plug–socket and cup–lid, and results indicate that the plug and socket with the large initial pose errors 145.4 mm, 43.8○ (the average errors of three axes) are successfully aligned with the allowed pose alignment errors 3.1 mm, 1.1○, and the cup and lid with the large initial pose errors 131.7 mm, 20.4○ are aligned with the allowed pose alignment errors −2.7 mm, −0.8○.

Relying solely on virtual springs and dampers, the transparency of standard virtual coupling suffers from the device-proxy coordination error when a large interaction force is engaged (e.g., contact tasks) and also from the unmodifiable inertias of the haptic device and the virtual proxy. To overcome these limitations, we propose a novel virtual coupling scheme, which, utilizing passive decomposition and a human force observer, can maintain the device-proxy coordination error even during contact tasks, while also allowing for scaling down (or up) the apparent inertia of the coordinated device-proxy system, thereby, substantially improving transparency of the standard virtual coupling. Experiments are performed to show the performance and passivity of the proposed virtual coupling. Minimum-possible passive inertia scaling is also theoretically established via some positive-real analysis.

During the past decade, robotics for cochlear implant electrode array insertion has been limited to manipulation assistance. Going beyond manipulation assistance, this paper presents the new concept of perception augmentation to detect and warn against the onset of intracochlear electrode array tip folding. This online failure detection method uses a combination of intraoperative electrode insertion force data and a predictive model of insertion force profile progression as a function of insertion depth. The predictive model uses statistical characterization of insertion force profiles during normal robotic electrode array insertions as well as the history of intra-operative insertion forces. Online detection of onset of tip folding is achieved using the predictive model as an input into a support vector machine classifier. Results show that the detection of tip folding onset can be achieved with an accuracy of 88% despite the use of intra-operative insertion force data representing incomplete insertion. This result is significant because it allows the surgeon or robot to choose a corrective action for preventing intra-cochlear complications.

On-line identification of soil parameters is a pre-condition of operating performance optimization and control for unmanned ground vehicles (UGV). Inverse calculation from measured vehicular operating parameters is a prevalent methodology. However, it inherently suffers from a multiple-solution problem caused by the coupling of soil parameters in terramechanics equations and an accuracy problem caused by the influences of state noise and measurement noise. These problems in tractive-force-related soil parameters identification were addressed here for air-cushioned vehicles (ACV) by taking advantage of their additional degree of control freedom in vertical force. To be specific, a g-function algorithm was proposed to solve the multiple-solution problem from reproductive tractive force equations; de-noising techniques consisting of mean-effect strategies, sampling points selection and sample rearrangement were employed to solve the accuracy problem. A series of experiments were conducted to evaluate these techniques at different noise levels and in different soil conditions. They got satisfactory results in terms of data utilization ratio, identification accuracy and performance stability. The contribution of the paper lies in inventing a novel algorithm for unique and accurate identification of tractive-force-related soil parameters without making any simplification to the original terramechanics equation and with robustness to variations of noise level and soil condition.

This note presents a novel method to design a controller for the formation of networked mobile robots, where the communication between the members of the group is affected by variable time-delay. The control objective is twofold: to maintain the formation during the motion along a desired path and guarantee no collisions with obstacles or adjacent robots. Initially, an innovative dynamical model is formulated for the system; afterwards, the notion of model predictive control is employed to ensure collision avoidance with guaranteed stability. Simulation results are provided to demonstrate the applicability and effectiveness of the suggested method.

A 2D path following control method for Autonomous Underwater Vehicles (AUVs) based on dynamic circle heading modification (DCHM) is presented. The method makes a dynamic auxiliary circle, whose radius depends on the cross-track error e, to intersect the desired path to get a new expected path point, and then determines a modified expected heading for the AUV. The guidance function is achieved by a direct mapping between e and the heading modification value Ψm. Several cases are tested in order to demonstrate the performance of the guidance and control method based on DCHMs for a real AUV. Results show that methods using a convex mapping function between e and Ψm based on our new idea can easily achieve a better convergence of path following, and reduce the error between the actual and desired heading angles. We can also customize a discretionary mapping between e and Ψm to get better path following performance.

This paper focuses on the problem of robust time-optimal trajectory planning of robotic manipulators to track a given path under a probabilistic limited actuation, that is, the probability for the actuation to be limited is no less than a given bound κ. We give a general and practical method to reduce the probabilistic constraints to a set of deterministic constraints and show that the deterministic constraints are equivalent to a set of linear constraints under certain conditions. As a result, the original problem is reduced to a linear optimal control problem which can be solved with linear programming in polynomial time. In the case of κ = 1, the original problem is proved to be equivalent to the linear optimal control problem. Overall, a very general, practical, and efficient algorithm is given to solve the above problem and numerical simulation results are used to show the effectiveness of the method.

For wheeled mobile robots moving in rough terrains or uncertain environments, driving failure will be encountered when trafficability failure occurs. Continuous mobility of mobile robots with special ability for overcoming driving failure on rough terrain has rarely been considered. This study was conducted using a four-wheel-steering and four-wheel-driving mobile robot equipped with a binocular visual system. First, quasi-static force analysis is carried out to understand the effects of different driving-failure modes on the mobile robot while moving on rough terrain. Secondly, to make the best of the rest of the driving force, robot configuration transformation is employed to select the optimal configuration that can overcome the driving failure. Thirdly, sliding mode control based on back-stepping is adopted to enable the robot achieve continuous trajectory tracking with visual feedback. Finally, the efficacy of the presented approach is verified by simulations and experiments.

This work presents a novel command strategy developed to improve operator performance and minimize difficulties in teleoperation tasks for mobile-manipulator systems with a holonomic base. Aimed specifically at novice operators, virtual fixtures are introduced as a means to minimize collisions and assist in navigation. Using the 6-degree-of-freedom (DOF) Omnibot mobile-manipulator system (MMS), a command strategy is implemented such that the operator need only control a 3-DOF haptic joystick to achieve full control of the Omnibot MMS. The command strategy is used to coordinate control between the arm and the base of the system, prevent collisions with known obstacles, and alert the operator of proximity to those obstacles with haptic forces. Through experimental testing it is shown that operator performance improved with the use of virtual fixtures.

A comparison of series, parallel, and dual Passive Assist Devices(PADs) designed using energy minimization based on a known maneuver is presented. Implementation of a PAD can result in an improvement in system performance with respect to efficiency, reliability, and/or utility. We introduce a new initial design using a weighted force displacement curve fit. A robust design approach for a family of maneuvers is developed and presented. Applications to a 3-link manipulator arm show that PADs could reduce energy consumption between 60% and 80%.

Type synthesis of spatial 3-DoF (degree of freedom) parallel mechanisms (PMs) with planar sub-chains is studied using the revised digital topology graph (r-DTGs) and arrays. First, many DTGs for type synthesis of spatial 3-DoF PMs are derived from their contracted graphs (CGs). Second, a complicated derivation of the DTG and an identification of an isomorphic DTG are transformed into a simple derivation of an array and an identification of an isomorphic array using a compiled program. Third, one or more spatial closed-loop chains in the derived DTGs are changed into the planar closed-loop chains by modifying digits marked in closed-loop chains, and the DTGs are transformed into the r-DTGs for the type synthesis of the spatial 3-DoF PMs with planar sub-chains. Finally, the 52 novel spatial 3-DoF PMs with the planar sub-chains are synthesized and verified by simulation mechanisms.

There was an error in the spelling of the author's affiliation. Where the affiliation read “Department of mechanical engineering, Mashad Branch, Islamic Azad University, Mashad, Iran” it should instead have read “Department of mechanical engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran”.

The publisher regrets this error.

A new approach to flow measurement and visualisation in fluid dynamics based on a group of perceptive communicating capsules has been developed. Experiments were carried out with fluid-mobilised and stationary capsules deployed in a fluid flow test rig (raceway pond). Each capsule contains a microcontroller, battery, infra-red and visible LEDs and other electronics. Using optical communications, capsules can record encounters with one another. From the resulting interaction patterns, fluid flow speed and path-frequency measurements were obtained. Additionally, the capsules have shown the capacity for distributed sensing, and their streaklines provide a valuable means of external visualisation.

In accordance with strict requirements of portability, cheapness, and modularity, an innovative assistive device for hand disabilities has been developed and validated. This robotic orthosis is designed to be a low-cost, portable hand exoskeleton to assist people with physical disabilities in their everyday lives. Referring to hand opening disabilities, the authors have developed a methodology which, by starting from the geometrical characteristics of the patient's hand, defines the novel kinematic mechanism that better fits to the finger trajectories. The authors have validated the proposed novel mechanism by carrying out a Hand Exoskeleton System (HES) prototype, based on a single-phalanx mechanism, cable driven. The testing phase of the real prototype with a patient is currently on going.

Cooperative ball juggling is one of the most difficult tasks when performed through autonomous robots. States of the ball (position and velocity) play a vital role for the stability and duration of a long rally. Cameras are normally used in ball juggling to calculate these parameters, the use of which is not only computationally expensive but also requires a lot of hardware to determine. In this paper, we propose a control loop for cooperative ball juggling using parallel DELTA robots without visual guidance. In contrast to using a visual system for ball states feedback, an observer based on the reflection laws is designed to calculate the continuous position and velocity of the ball during juggling. Besides the conventional controller blocks, the proposed control loop consists of the ball prediction and the plate striking movement generation blocks. Two controllers are designed for the stability and tracking of variable reference height of the ball during juggling: One controller calculates the velocity of the striking plate to achieve the reference height of the ball during juggling and the second controls the actuator angles. A simulation study and hardware experiments show applicability of the designed observer and validation of the proposed control loop.

The original version of this article listed the authors in the wrong order. The correct order is as follows:

He Xu, Yan Xu, Kaifeng Wang, X.Z. Gao, Khalil Alipour, Hongpeng Yu, Zhen Li, Ozoemena Anthony Ani.

The authors apologise for this error.