Zero moment point (ZMP) is the most popular concept that is applied to stabilize the gait motion of a biped robot. This paper utilizes ZMP with the augmented-reality (AR) method to improve the stability of gait motion of a biped robot. The 3ds Max computer software package is used to build a virtual robot. Under an achieved joint angle data of solid robot to produce an animation of the robot's trajectory, the joint angle data are transmitted to the virtual robot to analyze the offset of the trunk. Furthermore, this investigation adopts AR to allow the user to make direct comparisons between the solid and virtual robot before and after the gait motion is corrected. The animated trajectories of the virtual robot are compared and the relevant data provide feedback to the solid robot to adjust the joint angle and further correct its posture. The experimental results reveal that the proposed scheme can improve gait motion, even when the biped robot is affected by an unexpected loading disturbance. As well as improving the stability of gait motion of a biped robot, the results of this study can also be used to teach the application of the proposed method in a robotics class.

In this paper, we revisit the 3-degrees of freedom (DOF) pure translational mechanism. The mathematical model and the design considerations are discussed. A detailed sensitivity and error analysis is carried out and the results are discussed in a new perspective. The feasibility of the practical 3-DOF pure translational mechanism is established with novel design considerations to take care of theoretical mobility and geometrical constraints. We describe and validate the theoretical observations with stage-wise prototype models and experiments. The experimental results concur that all is well with 3-UPU in contrast to what is presented in refs. [6, 9, 10].

This paper investigates the kinematics and the optimization of a generic robotic structure composed by N serial rotary joints and actuated with a mono-directional tendon system. In the first part of the paper, the specific case that brought us to develop this study is introduced; the main motivations and the scenario with its specific constraints and design choices have been described.

Since a complete and detailed analysis of an n-R serial structure with this kind of characteristics could not be found in the literature, the study of the kinematics and the parameter optimization of such a structure is treated as generally as possible, in order to make the procedure and the results applicable for any similar structure. Finally, in the last part, through the introduction of specific constraints and the definition of the parameters, the general analysis has been applied to the specific case of study: the preliminary study of a finger exoskeleton for an astronaut suit.

The virtual decomposition control (VDC) is an efficient tool suitable to deal with the full-dynamics-based control problem of complex robots. However, the regressor-based adaptive control used by VDC to control every subsystem and to estimate the unknown parameters demands specific knowledge about the system physics. Therefore, in this paper, we focus on reorganizing the equation of the VDC for a serial chain manipulator using the adaptive function approximation technique (FAT) without needing specific system physics. The dynamic matrices of the dynamic equation of every subsystem (e.g. link and joint) are approximated by orthogonal functions due to the minimum approximation errors produced. The control, the virtual stability of every subsystem and the stability of the entire robotic system are proved in this work. Then the computational complexity of the FAT is compared with the regressor-based approach. Despite the apparent advantage of the FAT in avoiding the regressor matrix, its computational complexity can result in difficulties in the implementation because of the representation of the dynamic matrices of the link subsystem by two large sparse matrices. In effect, the FAT-based adaptive VDC requires further work for improving the representation of the dynamic matrices of the target subsystem. Two case studies are simulated by Matlab/Simulink: a 2-R manipulator and a 6-DOF planar biped robot for verification purposes.

Singularity-free workspace is a very important criterion for the design of manipulators, especially for parallel manipulators which are well known for their limited workspace and complex singularities. This paper studies geometric parameters and dexterity measures that affect the size of a singularity-free joint space and proposes methods for the development of 6-DOF Stewart–Gough parallel manipulators that have better singularity-free joint space. With a local dexterity measure as the objective function, a systematic method is employed to search for the design with a maximal singularity-free joint space. The related workspaces are also investigated. It is shown that the workspace is not proportional to the size of the joint space and that manipulators with a larger singularity-free workspace usually have relatively poor dexterity.

Push recovery is one of the most challenging problems for the current humanoid robots. The importance of push recovery can be well observed in the real environment. The critical issue for a humanoid is to maintain and recover its balance against any disturbances. In this research a new stereovision approach is proposed to estimate the robot deviation angle and consequently, the movement of center of mass of the robot is calculated. Then, two novel strategies have been devised to recover the balance of the humanoid which are called “knee strategy” and “knee-hip strategy.” Also, a mathematical model validates the efficiency of the proposed strategies as demonstrated in the paper. Experiments have been conducted on a humanoid robot and demonstrate that the predicted robot deviation angle, using stereovision technique, converges to the actual deviation angle. Stable regions of proposed strategies illustrate that the humanoid can recover its stability in a robust manner. Vision-based estimation also shows a higher correlation to actual deviation angle and a lower fluctuation compared with the output of the acceleration sensor.

This paper proposes a simple fuzzy sliding mode control to achieve the best trajectory tracking for the robot manipulator. In the core of the proposed method, by applying the feedback linearization technique, the known dynamics of the robot's manipulator is removed; then, in order to overcome the remaining uncertainties, a classic sliding mode control is designed. Afterward, by applying the TS fuzzy model, the classic sliding mode controller is converted to fuzzy sliding mode controller with very simple rule base. The mathematical analysis shows that the robot manipulator with the new proposed control in tracking the robot manipulator in presence of uncertainties has the globally asymptotic stability. Finally, to show the performance of the proposed method, the controller is simulated on a robot manipulator with two degrees of freedom as case study of the research. Simulation results demonstrate the superiority of the proposed control scheme in presence of the structured and unstructured uncertainties.

The absolute accuracy of a small industrial robot is improved using a 30-parameter calibration model. The error model takes into account a full kinematic calibration and five compliance parameters related to the stiffness in joints 2, 3, 4, 5, and 6. The linearization of the Jacobian is performed to iteratively find the modeled error parameters. Two coordinate measurement systems are used independently: a laser tracker and an optical CMM. An optimized end-effector is developed specifically for each measurement system. The robot is calibrated using fewer than 50 configurations and the calibration efficiency validated in 1000 configurations using either the laser tracker or the optical CMM. A telescopic ballbar is also used for validation. The results show that the optical CMM yields slightly better results, even when used with the simple triangular plate end-effector that was developed mainly for the laser tracker.

This paper presents a whole-body dynamics controller for robust push recovery on a force-controlled bipedal robot. Featherstone's spatial vector method is used to deduce dynamics formulas. We reveal a relationship between the accelerations of the floating base and the desired external forces needed for those accelerations. Introducing constraints on the desired external forces causes corresponding constraints on the accelerations. Quadratic programming is applied to find the extremal accelerations, which recover the robot from pushes as best as possible. A robustness criterion is proposed based on the linear inverted pendulum model to evaluate the performance of push recovery methods quantitatively. We evaluate four typical push recovery methods and the results show that our method is more robust than these. The effectiveness of the proposed method is demonstrated by push recovery in simulations.