Nonlinear couplings between the various joints of a robotic arm cause trouble in robot control. One possibility to overcome these difficulties is offered by the concept of nonlinear decoupling. The latter leads to independent linear SISO systems, each of them describing the movement of one joint. Thus, an application of control concepts for linear SISO systems is possible. However, at present such decoupling controls are computed from the mathematical model of the arm, the so-called drive equations, whereas actuator dynamics are considered only in a secondary way. In this paper the decoupling problem for robots is investigated by accounting also for the actuator dynamics from the very beginning. This results in decoupling laws requiring a complete state feedback, i.e. not only joint positions and velocities but also the states of the various actuators have to be used. Further, formulas are given which make the computation of those states unsuitable for direct measurements.

This paper presents a concept of sequentially actuated multi-degree-of-freedom (DOF) robot with only one motor. A switching mechanism allowing to actuate sequentially the different joints–or combinations of the joints–of the robot is also proposed. Potential actuation schemes (joint combinations) are presented and their properties are discussed. Cartesian pick-and-place trajectories are then considered using different actuation schemes. An optimisation algorithm is presented in order to provide the best possible sequence by minimising the amplitude of the joint rotations for a given actuation combination. A simple planar two-DOF and the SCARA architectures are used to illustrate the concept. Finally, a prototype is developed with the aim of demonstrating the sequentially actuated manipulator concept.

The purpose of the present study is to assess the effect of an auxiliary lateral image and display devices on manipulation performance in a virtual reality-based hand rehabilitation system. The system consists of a personal computer, a tracker, a data glove, and a display device. For this study, a projector, a monitor, and a head-mounted display were respectively used as the display devices to present three-dimensional virtual environments. Twelve volunteers were recruited to take a pick-and-place procedure at different levels of difficulty. Task time and collision frequency were the parameters used to evaluate the manipulation performance. It was found that the presence of an auxiliary lateral image was a significant factor only for the performance of the projector group and the monitor group. In addition, no statistically significant difference was found in the comparison between the projector group and the monitor group.

The four papers encompassing this special section on Robot Mediated Neuro-motor Therapy introduce a new area for robotics in the healthcare industry, that of assisting in the delivery of neuro-motor therapies, for patients recovering from a stroke. As life expectancy increases, so do problems associated with old age. In the paper by Krebs et al. the authors not only summarise the need for action in stroke rehabilitation but also makes a useful distinction between assistive technologies that provide enhanced abilities for the patient, and therapy tools for the clinician, that seek to enhance the patients recovery.

This article proposes an observer design for two important variables in the studies of single-leg hopping robot (SLHR), the apex height, and the vertical velocity of SLHR during its stance phase. At first, the Euler–Lagrange (EL) dynamics of SLHR are obtained and apex height is identified in the state-space representation of the EL dynamics. Apex height is the state variable that represents the robot body’s height at the top point, which keeps on changing as the robot functions. Vertical velocity is the velocity of the robot in the vertical direction. An observer design is presented in this article which will estimate these variables when required. The quality of the estimation is validated by the simulation results where the estimation error is zero which means the model output is correct and observer performance is good.

The attitude control error of the robot end-effector directly affects the manufacturing accuracy. The study aims to develop a real-time measurement method of the industrial robot end-effector attitude in the field environment for improving the control accuracy of robot attitude.

In this paper, an attitude measurement method of robot end-effector based on the inertial technology was proposed. First, an inertial measurement system was designed, and the measurement parameters and installation errors were calibrated. Then the inertia measurement principle of robot end-effector attitude was explored, and the robot end-effector attitude measurement was realized with the fourth-order Runge−Kutta algorithm. In addition, the influence of the data processing algorithm and sampling frequency on the attitude accuracy was analyzed. Finally, a test platform was built to experimentally explore the proposed inertial measurement method.

The inertial measured data were compared with the data obtained with the laser tracker. The measurement accuracy of the inertial measurement method reached 0.15°, which met the accuracy requirements of real-time measurements of robot end-effector attitude in the manufacturing field.

The method proposed in this paper is convenient and can realize the real-time attitude measurement of industrial robot. The measurement results can compensate the attitude control error of the robot end-effector and improve the attitude control accuracy of the robot.

The objective of this work is to construct a robot that is based on 3D printing to meet the low-cost and light structures. The Computer-aided-design model is used with LabVIEW to simulate the given trajectory. Users of the simulation of such methodology can preview the simulated motion and perceive and resolve discrepancies between the planned and simulated paths prior to execution of a task. The advantages of this study are the lack of need to mount extra sensors on realistic robot to measure joint space coordinates, simplifying the hardware. These outcomes can also be used in an undergraduate robotics course.

In dynamically switched systems with unknown switching signal, the control system is conventionally designed based on the worst switching scenario to ensure system stability. Such conservative design demands excessive control effort in less critical switching configurations. In the case of continuum mechanics systems, such excessive control inputs result in increased structural deformations and resultant modeling uncertainties. These deformations alter differential equations of motion which cripple the task of control. In this paper, a new approach for tracking control of uncertain continuum mechanics multivariable systems undergoing switching dynamics and unknown time delay has been proposed. Control algorithm is constructed based on the mathematical rigid model of the plant and a Common Lyapunov Function (CLF) is proposed upon sliding hyperplane regarding all switching configurations. Considering the model-based nature of sliding mode control (SMC) and inevitable uncertainties induced from modeling simplifications of continuum system or parameter evaluation errors, Finite Element Analysis (FEA) is utilized to approximate total model uncertainties. To obtain robust stability, instead of conventional switching functions in the construction of control law, the control inputs are selected such that system dynamics reside within stability bounds which are calculated based on the Lyapunov asymptotic stability criterion. Therefore, the unwanted chattering issue caused by continuous switching is not observed in control input signals. Eventually, the accuracy of the proposed method has been verified through the student version of ANSYS® mechanical APDL-based simulations and its effectiveness has been demonstrated in multiple operating conditions.

Multi-legged robots with rigid-flexible coupling grippers have appealing applications to asteroid exploration with the microgravity. However, these robots usually have significantly complicated structures, which leads to a great challenge for the kinematic design.This paper proposes the kinematic design method for a novel multi-legged robot with the microspine gripper. First, the structure of the multi-legged asteroid exploration robot and the microspine gripper are demonstrated. Second, four performance evaluation indices, which are used to evaluate the stiffness, velocity, motion / force transfer efficiency and gripper attachment efficiency of the robot, are derived from the kinematic model. Non-dimensional design spaces of parameters to be optimized are drawn, and performance atlases are presented in design spaces. Third, the stiffness model of the microspine is derived. In addition, the constraint condition of the restoring spring is established, and the stiffness of restoring springs are optimized using the genetic algorithm. Several experiments are conducted to verify the stiffness model of the microspine. Finally, the prototype is developed and the experimental results validates the kinematic design method.

In the paper, a new adaptive control law for controlling robot manipulators is derived based on the Lyapunov theory; trigonometric functions are used for the derivation of the parameter estimation law. In this note, we have derived a logarithmic parameter estimation law based on a previous paper, and the boundedness of tracking error has been shown.

With the progress of industry, people are facing more and more complicated tasks, which cannot be completed by conventional rigid robot. For this, a deployable robot based on spherical linkage parallel mechanism was proposed to satisfy relevant requirements for the degrees of freedom in this study. Based on the design of robot model and its control box, a mathematical model for the robot was established, and the relationship between motion space and drive space was deduced accordingly. Subsequently, a control system consisting of the upper and lower computers was introduced. Two control modes, that is, Joystick control and remote control, were developed. The upper computer control interface for the robot was completed by MATLAB construction. At last, the two control modes as well as autonomous detection were demonstrated by motion test. This achievement will further advance the applications of deployable robot in job aid and intelligent exploration.

For design using digital human models, human anthropometry data are required as input and are extracted from measurements. There is inherent error associated with these measurements which impacts the output of the simulation. Current techniques in digital human modeling applications primarily employ deterministic methods which are not well suited for handling variability in anthropometric measurement. An alternative to deterministic methods is probabilistic/sensitivity analysis. This study presents a probabilistic sensitivity approach to gain insights into how uncertainty in anthropometric measurements can affect the results of a digital human model with the specific application of vehicle-related reach tasks. Sensitivity levels are found to determine the importance of variability in each joint angle and link length to the final reach. A55-degree of freedom (DOF) digital human model is introduced to demonstrate the sensitivity approach for reach tasks. Seven right-hand reach target points and two left-hand reach target points (creating a total of 14 reach tasks) within a vehicle are used to compare the sensitivities in the joint angles and link lengths resulting from measurement uncertainty. The results show that the importance of each joint angle or link length is dependent on the characteristics of the reach task and sensitivities for joint angles, and link lengths are different for each reach task.

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.

This paper describes the development of a desktop robotic system that enables the plug-and-play function through the USB (universal serial bus) port of a personal computer (PC). Thus a new kind of desktop PC peripheral is invented that has programmable manipulability. The robotic system is realized on an internally distributed control structure that facilitates higher system reliability. A PID control algorithm is implemented on a prototype of the proposed system, to demonstrate the system's ability to implement feedback control. Experimental results show the performance and properties of the proposed system.

A laser range finder mounted on a site and azimuth turret is used as a 3D range camera. It forms, associated with a video camera, an original stereovision system. The internal structure of both images are the same but the resolution of 3D image stays low. By ignoring the acquiring speed of measures, spatial resolution is limited by the accuracy of deviation device and the laser footprint. The fact that the impact of the beam is not a point introduces spatial integration.

To correct the average at depth discontinuities due to the beam footprint, a neural-network-based solution is reported.

The use of such a multisensor system requires its calibration. As camera calibration is a well-known problem, the paper focuses on models and calibration methods of the range finder. Experimental results illustrate the quality of the calibration step in terms of accuracy and stability.

The footprint correction is evaluated for both 1D and 2D range finder scannings.

The following corrections to the paper by Zhang et al.1 should be noted. The corrected paper follows this notice.

The title of the originally published paper should be corrected to “Design and analysis of a 3-DOF spherical parallel manipulator.”

It is very challenging for robots to perform grinding and polishing tasks on surfaces with unknown geometry. Most existing methods solve this problem by modeling the relationship between the force sensing information and surface normal vectors by analyzing the forces on special end tools such as spherical tools and cylindrical tools and simplified friction model. In this paper, we propose a normal vectors learning method to simultaneously control end-effector force and direction on unknown surfaces. First, the relation that mapping the force sensing information to the surface normal vectors is learned from the demonstrated data on the known plane using locally weighted regression. Next, the learned relation is used to estimate surface normal vectors on the unknown surface. To improve the force control precision on the unknown geometry surface, the adaptive force control is developed. To improve the direction control precision due to friction, the iterative learning control is developed. The proposed method is verified by comparative simulations and experiments using the Franka robot. Results show that the end-effector can be controlled perpendicular to the surface with a certain force.

The control of industrial robot manipulators presents a difficult problem for control engineers due to the complexity of their nonlinear dynamics models. Nonlinear controls based on feedback linearization are developed to meet control requirements. Model-based nonlinear control is highly sensitive to parameter errors and leads to problems of robustness for tracking trajectories at high speeds, and there is the additional problem of a heavy computational burden to consider in the design of nonlinear controllers. In this paper, a mechatronic design approach is proposed, which aims to facilitate controller design by redesigning the mechanical structure. The problem is approached in two steps: first, the dynamic decoupling conditions of manipulators are described and discussed, involving redistribution of the moving mass, which leads to the decoupling of motion equations. A classical linear control law is then used to track the desired efficient bang-bang profile trajectory. Then, in the presence of parameter uncertainty and external disturbances, the nonlinear controls with simple structures are adopted to stabilize the decoupled system asymptotically. An analysis of the results from a simulation of this approach demonstrates its effectiveness in controller design. The proposed improvement in control performance is illustrated via two spatial manipulators.