This paper proposes a modular method based on the kinematics of serial manipulators to synthesize over-constrained mechanisms. Because the PPP manipulator has an unlimited work space, its end-effector can be constrained to trace a trajectory identical to those of another open-chain manipulator, including a P joint single link and an RR dyad. In doing so, two open-chain manipulators can be concatenated to form closed-loop mechanisms, including PPPP, PPPRR, or PPCR mechanisms. To design over-constrained mechanisms efficiently, the Denavit–Hartenberg convention is adopted to describe the PPP manipulator kinematically, and the Euler angles are utilized to derive geometric constraints of synthesized over-constrained mechanisms. Next, kinematic equations of the PPP manipulator can be modularized and applicable to analyze different closed-loop mechanisms. At last, by adjusting link lengths, twisted angles, and joint angles of the synthesized PPPRR and PPCR mechanisms to form other over-constrained mechanisms configurationally. The novelty of this research lies in modularizing the over-constrained mechanism into two movable serial manipulators whose end-effectors share identical trajectory and orientation. Thus, defining geometrical constraints of the over-constrained mechanism can be transformed into finding angular parameters describing the orientation of these two serial manipulators such that the end-effector coordinate system of two manipulators can properly be aligned. Angular parameters of the serial manipulators can be easily determined by means of Euler angles, which yields an advantage of easy calculation since it only involves the computation of Euler angles parameters. The presented method can be extended to the kinematic synthesis and analysis of more spatial closed-loop mechanisms.

In this paper, an automatic obstacle avoidance trajectory planning strategy is proposed for the simultaneous motion of multi-robots, which perform anthropomorphic skill operations in a large curved preformed three-dimensional (3D) weaving environment with multiple obstacles and limited space, to eliminate tedious manual calibration work of robot path in engineering. Firstly, an Adaptive Goal-guided Rapidly-exploring Random Trees (AGG-RRT) algorithm is proposed, combined with the robot obstacle avoidance strategy, to search the discrete position of the collision-free path of the end-effector gradually from the starting point to the ending point. Then the optimization of the path is completed by bidirectional pruning of redundant nodes and cubic non-uniform rational B-spline (NURBS) curve fitting. And finally, the robot trajectory is interpolated based on S-shaped acceleration/deceleration planning to ensure smooth robot joint motion. The simulation results demonstrate the superiority of the AGG-RRT algorithm over the basic RRT algorithm and related improved algorithms in terms of search time and success rate. The simulated experiments also achieve the smooth trajectory planning of multiple robotic arms with the synchronous obstacle avoidance motion, which shows that the AGG-RRT algorithm is successfully applied and the collision-free trajectory planning strategy is effective.

Stroke has a considerable incidence in the world population and would cause sequelae in the upper limbs. One way to increase the efficiency in the rehabilitation process of patients with these sequelae is through robot-assisted therapy. The present study developed a portable robotic orthosis called Pinotti Portable Robotic Exoskeleton (PPRE) and validated its functioning in clinical tests. The static and dynamic parts of the device modules are described. Design issues, such as heavyweight and engine positioning, have been optimized. The implementation of control was through a smartphone application that communicates with a microcontroller to perform desired movements. Four individuals with motor impairment of the upper limbs due to stroke performed clinical tests to validate the device. Participants did not mention pain, discomfort, tingling, and paresthesia. The robotic device showed the ability to perform the flexion and extension movements of the fingers and elbow. The PPRE was confirmed to be adequate and functional at different levels of motor impairment assessed. The orthosis presented advantages over the currently existing devices, concerning its biomechanical functioning, portability, comfort, and versatility. Thus, the apparatus has the great innovative potential to become a device for home use, serving as an aid to the therapist and facilitating the rehabilitation of patients after an injury. In a larger sample, future studies are needed to assess the effect of a robotic orthosis on the level of rehabilitation in individuals with upper limb impairment.

Mobile robots and multimobile robotic system usage for task achievement have been an emerging research area since the last decades. This article presents a review about mobile robot navigation problem and multimobile robotic systems control. The main focus is made on path planning strategies and algorithms in static and dynamic environments. A classification on mobile robots path planning has been defined in the literature and divided to classical and heuristic approaches. Each of them has its own advantages and drawbacks. On the other hand, the control of multimobile robots is presented and the control approaches for a fleet of robots are presented. Scientists found that using more than one robot as opposed to a single one presents many advantages when considering redundant task, dangerous tasks, or a task that scales up or down in time or that requires flexibility. They have defined three main approaches of multiple robots control: behavior-based approach, leader–follower approach, and virtual structure approach. This article addresses these approaches and provides examples from the literature.

The safety and reliability of robots are very important for the inspection in a long-distance pipeline used for the oil and gas transportation. In this paper, the long-distance pipeline pig and robots (LDPPRs) are classified into two categories, which are velocity-uncontrollable type and velocity-controllable type. Among them, the velocity control of velocity-controllable LDPPR has three ways, which are friction resistance, driving force, and self-running. Meanwhile, the mechanical models of the motion of the LDPPRs are classified into the dynamic model of the velocity-uncontrollable LDPPRs, velocity-controllable LDPPRs, and vibration, and the contact mechanics model between the rubber barrel and the pipe wall. In addition, the anti-stuck technologies, the inspection technologies, and the location technologies are investigated and analyzed. Thus, the purpose of this review is to provide a concise reference for the development and research directions, as well as the design of the LDPPRs.

An approach for calculating the effective workspaces of parallel mechanisms has been considered in this paper. The effective workspace is a set of reachable by the end-effector points, where an important parameter (or parameters) from the point of view of operation is not higher than critical. In this article, the speed and torque in the drive and the stiffness of the mechanism are considered as such parameters. An approach to determining the appropriate effective workspace is presented for each parameter. The optimization process, which is based on presented methods, allows one to choose basic technical solutions of the designed robot: the links (lengths and cross-sections), the drives, and types of hinges, which guarantee its operability at the specified operational characteristics. Case studies of a delta robot with four degrees of freedom and a planar five-bar mechanism are presented for testing these approaches. The presented methods are of great practical importance because it uses movement parameters or operational characteristics that are decisive for this mechanism and have clear physical meaning.

On-orbit servicing and active debris removal missions will rely on the use of unmanned satellite equipped with a manipulator. Capture of the target object will be the most challenging phase of these missions. During the capture manoeuvre, the manipulator must avoid collisions with elements of the target object (e.g., solar panels). The dynamic equations of the satellite-manipulator system must be used during the trajectory planning because the motion of the manipulator influences the position and orientation of the satellite. In this paper, we propose application of the bidirectional rapidly exploring random trees (BiRRT) algorithm for planning a collision-free trajectory of a manipulator mounted on a free-floating satellite. A new approach based on pseudo-velocities method (PVM) is used for construction of nodes of the trajectory tree. Initial nodes of the second tree are selected from the set of potential final configurations of the system. The proposed method is validated in numerical simulations performed for a planar case (3-DoF manipulator). The obtained results are compared with the results obtained with two other trajectory planning methods based on the RRT algorithm. It is shown that in a simple test scenario, the proposed BiRRT PVM algorithm results in a lower manipulator tip position error. In a more difficult test scenario, only the proposed method was able to find a solution. Practical applicability of the BiRRT PVM method is demonstrated in experiments performed on a planar air-bearing microgravity simulator where the trajectory is realised by a manipulator mounted on a mock-up of the free-floating servicing satellite.

The inertial parameters of payloads attached to the end effector of robots benefit to several robotics applications, such as the model-based control, the task optimization, and so on. These applications require the accurate estimation of the inertial parameters. In the existing payload estimation approaches, however, the data weighting technique, which can reduce the adverse effects of outliers and significantly improve the final results, has not been applied yet. In this article, an accurate identification method based on double weighting for inertial parameters of robot payloads is proposed. In order to obtain the weighting matrices, a modified dynamic parameter identification method with two loops is firstly proposed. Then, based on the identified results of dynamic parameters, a payload identification model based on double weighting is constructed. In addition, the variations of both nonlinear friction parameters and linear friction parameters caused by the payload are considered in this model. Finally, experimental comparisons between our method and another four methods are conducted. The results confirm that our method shows the best performance, especially on improving the identification accuracy of mass and center of mass of the payload.

The purpose of this study is to realize virtual interaction and manipulation control of a hexacopter based on hand gesture recognition from a designed data glove, to provide an intuitive and visual real-time simulation system for flight control algorithm verification and external control equipment testing. First, the hand gesture recognition from a designed data glove is studied, which can recognize different actions, such as mobile ready, grab, loosen, landing, take-off, and hover. Then, the design of virtual simulation system for hexacopter capture is completed, with the model design of hexacopter and manipulator, and the simulation software design with $CoppeliaSim$ . Finally, virtual simulation experiment of hexacopter grasping and virtual flight control experiment based on data glove are tested, respectively, and quantitatively described. The overall recognition rate is 84.3%, indicating that the data glove produced has the ability to recognize gestures, but its recognition performance is not superior. In gesture recognition, the recognition rate of static gestures is relatively higher than that of dynamic gestures. Among the static gestures, the hover gesture has the highest recognition rate. The average correct rate of static gestures can reach 94%. The lowest recognition rate of dynamic gestures is upward movement, and the average recognition rate of dynamic gestures is 76.1%. The research can be used to remotely operate hexacopter using a data glove in the future and improve the control performance through virtual interaction and manipulation simulation before actual application.

Aiming at the problem of low accuracy of robot joint fault diagnosis, a fault diagnosis method of robot joint based on BP neural network is designed. In this paper, the UR10 robot is taken as the research object, and the end pose data of the robot are collected in real time. By injecting different joint errors and changing the sampling frequency, the joint fault database is collected and established, and the BP neural network is used for training to obtain the robot neural network fault diagnosis model. The fault diagnosis model can output the joint fault of the input end pose data. And we analyzed the influence of different joint angle errors and different training sets on the accuracy of joint fault diagnosis of the robot. The results show that when the sampling frequency is 250 Hz, the simulation result of joint fault diagnosis accuracy with the fault degree of 0.5° is 99.17%, and the experimental result is 97.87%. Compared with traditional data-driven methods, it has higher accuracy and diagnostic efficiency, and compared with existing machine learning methods, it also achieves a high accuracy while reducing the network complexity. The effectiveness of the BP neural network robot joint fault diagnosis method is verified by experiments.

Productivity can be increased by manipulators tracking the desired trajectory with some constraints. Humans as moving obstacles in a shared workspace are one of the most challenging problems for cable-driven parallel mechanisms (CDPMs) that are considered in this research. One of the essential primary issues in CDPM is collision avoidance among cables and humans in the shared workspace. This paper presents a model and simulation of a reconfigurable, fully constrained CDPM enabling detection and avoidance of cable–human collision. In this method, unlike conventional CDPMs where the attachment points are fixed, the attachment points on the rails can be moved (up and down on their rails), and then the geometric configuration is adapted. Karush–Kuhn–Tucker method is proposed, which focuses on estimating the shortest distance among moving obstacles (human limbs) and all cables. When cable and limbs are close to colliding, the new idea of reconfiguration is presented by moving the cable’s attachment point on the rail to increase the distance between the cables and human limbs while they are both moving. Also, the trajectory of the end effector remains unchanged. Some simulation results of reconfiguration theory as a new approach are shown for the eight-cable-driven parallel manipulator, including the workspace boundary variation. The proposed method could find a collision-free predefined path, according to the simulation results.

Due to the merits of high rigidity and good dynamics, hybrid machine tools have been gradually applied to efficient machining of thin-walled workpiece with complex geometries. However, the discontinuity of tangential component of toolpath in hybrid machine tools may cause velocity fluctuations, leading to poor surface quality of workpiece. In this paper, a novel 5-axis hybrid machine tool is taken as an example to demonstrate a smooth toolpath interpolation method. First, an adaptive acceleration and deceleration control algorithm is presented to realize the smooth transition between two constrained velocity points. Second, a spline curve-based interpolation algorithm is proposed to realize the smoothness of the trajectory. Meanwhile, a parameter synchronization method is proposed to ensure the synchronization of the interpolated tool-axis vector and the interpolated tool tip. Thirdly, an inverse kinematic analysis is conducted based on an inverse position solution model and a velocity mapping model. Finally, a set of machining tests on S-shape workpiece in line with the ISO standard is carried out to verify the effectiveness of the proposed smooth toolpath interpolation method.

Configurable platforms bring a research field to expand the attributes of parallel manipulators. This work is devoted to investigate the kinematics of a nine-degrees-of-freedom parallel manipulator whose active kinematic pairs are located near to the fixed platform, and it is equipped with a 6-R configurable platform. The mobility of the proposed 9-UPUR{6R} configurable parallel manipulator is such that it is possible to manipulate the kinematics of a grasping triangle associated to the configurable platform. The theory of screws is systematically applied to solve the direct and inverse infinitesimal kinematics of the manipulator. As an intermediate step, the displacement analysis is approached by means of algebraic geometry. The contribution is complemented with numerical examples to illustrate the versatility of the method of kinematic analysis.

This article is concerned with remote monitoring and control of the 2-degrees of freedom (DoF) robotic manipulators, which have nonlinear dynamics over the packet erasure channel, which is an abstract model for communication over the Internet, WiFi, or Zigbee modules. This type of communication is subject to imperfections, such as random packet dropout and rate distortion. These imperfections cause a significant challenge for monitoring and control of robotic manipulators in the industrial environments because sensitive data, such as sensor data and control commands may not ever reach to their destination resulting in significant performance degradation. Therefore, the effects of these imperfections must be compensated. In this article, we apply two coding and control techniques previously developed for the telepresence ad teleoperation of autonomous vehicles to compensate the effects of the above communication imperfections for remote monitoring and control of the 2-DoF robotic manipulators controlled over the packet erasure channel. To achieve this goal, we design a new linear controller and a new nonlinear controller for the 2-DoF robotic manipulators over the packet erasure channel. The first technique is based on the linearization method and the second technique uses a nonlinear controller. The performances of these two techniques for remote monitoring and control of robotic manipulators are evaluated and compared with each other in this paper. We illustrate their satisfactory performances in the presence of severe communication imperfections.

A spring-assisted modular and reconfigurable robot (SA-MRR) has been recently developed at our laboratory to reinforce its performance and enable safe and dexterous operation in human–robot environments. Multiple working mode (MWM) control enables each SA-MRR joint module to switch independently between working in a primary actuation mode and a secondary, spring-assisted mode that may improve task-specific energy performance measures and safety in a variety of manipulation tasks. The spring-assisted mode is characterized by synergy of spring and motor energy and may be summoned to offset motor energy demands or to safeguard a reconfigurable set of secondary joint limits. In this research work, two spring-assisted working mode strategies are proposed, and their characteristics have been investigated for SA-MRR actuation energy advantages while safe robot segregation in collaboration tasks is maintained. One MWM strategy has been designed to safeguard task-specific joint limits and is able to decrease motor energy consumption in some tasks. Another MWM strategy has been designed for energy efficiency and was able to reduce motor energy per cycle by $ \text{72}$ % in a simulated manipulation task while maintaining spatial safety constraints. Numerical simulations have demonstrated the effectiveness of the proposed spring-assisted working mode strategies for energy-aware safe manipulation applications.

Early-stage rehabilitation therapy for post-stroke patients consists of intensive and accurate training sessions. During these sessions, the therapist moves the patient’s joint within its range of motion repetitively. Patients, at this stage, often cannot control their muscles, and neurological disorders may occur and lead to undesirable movements. Thus, the therapist should train the joint gently to handle any sudden involuntary movements. Otherwise, the joint may undergo excessive torques, which may injure it. In this paper, we address this case and develop a clinical rehabilitation robotic system for training the knee joint taking into account the occurrence of these undesirable movements. The developed system has an innovative mechanism to measure interaction torques exerted by involuntary movements. Then, we introduce a new control approach consisting of an admittance controller and a proportional-derivative controller augmented by a radial basis function (PD-RBF) neural network. The PD-RBF guides the robot joint along a predefined trajectory, while the admittance part tracks any sudden interaction torques and updates the predefined trajectory accordingly. Thus, the robot trains the knee joint and once an undesirable movement occurs the robot gets along with this movement smoothly, then it gets back to the predefined trajectory. To validate the performance of the proposed admittance PD-RBF controller, we consider two controllers, an admittance adaptive sliding mode control and an admittance conventional PD one. Then, a compatarive study is conducted on these controllers via real-world experiments. The obtained results verify the efficiency of the admittance PD-RBF and prove its superiority over the other aforementioned controllers.

In this work, a vision-based guidance algorithm for interception of an aerial manoeuvring target is proposed. Vision-based aerial engagement in 3D space in an outdoor environment is challenging due to uncertainty in estimating the target location. The vision-based guidance algorithm proposed here generates the desired velocity commands for the interceptor drone based on the orientation of the target pixel in the image plane. The desired velocity at the centre of gravity of the interceptor is calculated such that the velocity at the camera centre is aligned towards the line joining the target pixel and the camera centre. It is shown that the proposed guidance strategy forces the target pixel towards the centre of the image plane and leads to low miss distance. The algorithm developed is first tested in the ROS-Gazebo platform and then implemented in field experiments.

This paper presents an investigation of the effectiveness of different inverse kinematics strategies in a context of physical human-robot interaction in which passive articulated shells are mounted on the links of a serial robot for manual guidance. The concept of passive link shells is first recalled. Then, inverse kinematics strategies that are designed to plan the trajectory of the robot according to the motion sensed at the link shells are presented and formulated. The different approaches presented all aim at interpreting the motion of the shells and provide an intuitive interaction to the human user. Damped Jacobian based methods are introduced in order to alleviate singularities. A serial 5-dof robot used in previous work is briefly introduced and is used as a test case for the proposed inverse kinematics schemes. The robot includes two link shells for interaction. Simulation results based on the different inverse kinematic strategies are then presented and compared. Finally, general observations and recommendations are discussed.

Every year the shortage of biosamples is increasing, while the requirements for their quality are constantly tightening, which requires the introduction of new technological solutions. To solve these problems, a robotic system for aliquoting biological liquid was developed. The aliquotation process is described. The station includes a serial robot on which a gripper based on a globoid worm is installed. The gripping device is parameterized and takes into account the gripping force for different finger deflections. 3D models were developed using Computer Aided Design (CAD) system tools, after which working layouts were created using 3D printing. The design process and test results are discussed to show the efficiency of the built prototype with lab tests.

For diagnostic and therapeutic applications in spacious spots of the gastrointestinal (GI) tract, the single rigid body capsule clinically applied is difficult to realize the fix-point posture adjustment function manipulated by the external permanent magnet system using the static balance control because the posture alignment and the locomotion interfere with each other. To realize this function easily, the dual hemisphere capsule robot (DHCR) is proposed, based on tracking effect—the axis of DHCR keeps tracking the normal orientation of the spatial universal rotating magnetic vector (SURMV). Since tracking effect employs dynamic balance control, dynamic stability of the DHCR system affects posture alignment performance. This paper focuses on posture alignment dynamic modeling and the influence of the magnetic flux density and the angular velocity of the SURMV, along with the damping coefficient of the GI tract surface on stability, obtaining the stability domains of parameters. Furthermore, to reduce error due to the uncertainties in complex GI tract environment, the sliding mode controller based on nominal model is proposed to achieve more accurate dynamic tracking, and Lyapunov theorem is employed to assess stability of controller. Finally, the tracking effect is verified through simulations and experiments, indicating that the fix-point posture adjustment can be realized with higher accuracy and efficiency.