BACKGROUND: Stroke is the most prevalent neurological disease and often leads to disability. Stroke can affect a person’s daily life, for example, its typical feature is the decline in the patient’s upper limbs. In order to reduce the sports injury of stroke patients, the best method is to carry out certain rehabilitation training. OBJECTIVE: In this paper, inverse kinematic analysis and trajectory planning of a modular upper limb rehabilitation exoskeleton are proposed. METHODS: The reverse coordinate system method is applied to solve inverse kinematics of the exoskeleton with a non-spherical joint in the wrist. For verifying the effectiveness of the algorithms, the smooth round-trip trajectory movement in joint place is designed and simulated. RESULTS: The reverse coordinate system method can simplify the calculation process compared with the normal coordinate system. Smooth round-trip trajectory planning is simulated to generate a smooth trajectory curve. CONCLUSIONS: The developed inverse kinematics algorithm and trajectory planning method are effective.

Magnetic adsorption mechanisms are widely used for wall-climbing robots to manipulate a locomotive on the surface of a magnetic conducting metal. However, the reported magnetic adsorption mechanisms are subject to the problems such as the lack of adsorption capability, the weakness of kinematic performance, and the overwhelming detaching force. To solve the problems, a novel style of a permanent-magnetic adsorption mechanism using an electromagnetic method and internal force compensation principle is detailed in this work. Specifically, a permanent magnet, an electromagnet, and a nonlinear spring are configurated to achieve a reliable adsorption function by using the minimal detaching force. Following that, the results obtained from both the finite element analysis and the experiments carried out by using a prototype demonstrated its effectiveness. It does not only have a rapid and controllable adsorption-detachment capacity in reference to the magnetic conducting surface but also has low power consumption, large adsorption force, and reliable and safe performance.

This paper focuses on the problem of extracting the physical dynamic parameters which are fundamental for computing the positive-definite link mass matrix. To solve this problem, a minimal set of dynamic parameters were firstly identified by the standard least squares method. In order to simplify the dynamics model, a new set of essential dynamic parameters were calculated by eliminating the poorly identified parameters with an iterative approach. Based on these dynamic parameters with better identification quality, a universally global optimization framework was proposed here to retrieve the set of physical dynamic parameters of a serial robot, in which parameter bounds, linear and nonlinear constraints with physical consistency can be easily considered, such as the triangle inequality of the link inertia tensors, the total link mass limitations, other user-defined constraints and so on. Finally, validation experiments were conducted on the KUKA LBR iiwa 14 R820 robot. The results show that the proposed optimization framework is effective, and the identified dynamic parameters can predict the robot joint torques accurately for the validation trajectories. INDEX TERMS dynamic parameter identification, physical parameters, nonlinear global optimization, KUKA LBR iiwa robot.

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Robot joint friction is an important and complicated issue in improving robot control performance. In this paper, a virtual sensor based on the total generalized momentum concept is proposed to estimate the total friction torque, including both the motor-side and link-side friction, of robot joints without joint torque sensors. The proposed algorithm only requires a robot joint dynamics model and not a complex friction model dependent on factors such as time and velocity. By compensating for the estimated friction torque with a robot joint controller, the trajectory tracking performance of the controller, especially the velocity tracking performance, can be improved. To verify the effectiveness of the developed algorithm, 2-DOF planar manipulator simulations and single-joint system experiments are conducted. The simulation and experimental results show that the designed virtual sensor can effectively estimate the total joint friction disturbance and that the controller trajectory tracking performance is improved after observed friction compensation. However, the position tracking performance improvement of the controller is less than that for the velocity tracking performance improvement during the experiments. In addition, the velocity step response ability and velocity tracking performance of the controller are improved more at low velocities than that at high velocities in the experiments. The proposed algorithm has engineering and theoretical significance for estimating robot joint friction and improving the performance of robot joint controllers.