This paper aims at developing a novel method to assess the kinematic reliability of robotic manipulators based on the fuzzy theory. The kinematic reliability quantifies the probability of obtaining positioning errors within acceptable limits. For this purpose, the fuzzy reliability evaluates the effect of the joint clearances on the end-effector position to compute a failure possibility index. As an alternative to the conventional methods reported in the literature, this failure possibility index conveys a novel assessment of the kinematic performance. The numerical results are compared with the well-known probabilistic approach based on the Monte Carlo simulation.

In this article, we improve the efficiency of a turbine blade inspection robotic workcell. The workcell consists of a stationary camera and a 6-axis serial robot that is holding a blade and presenting different zones of the blade to the camera for inspection. The problem at hand consists of a 6-DOF (degree of freedom) continuous optimization of the camera placement and a discrete combinatorial optimization of the sequence of inspection poses (images). For each image, all robot configurations (up to eight) are taken into consideration. A novel combined approach is introduced, called blind dynamic particle swarm optimization (BD-PSO), to simultaneously obtain the optimal design for both domains. The objective is to minimize the cycle time of the inspection process, while avoiding any collisions. Even though PSO is vastly used in engineering problems, the novelty of our combinatorial optimization method is in its ability to be used efficiently in traveling salesman problems where the distances between the cities are unknown and subject to change. This highly unpredictable environment is the case of the inspection cell where the cycle time between two images will change for different camera placements.

In typical calibration methods (kinematic or non-kinematic) for serial industrial robot, though measurement instruments with high resolutions are adopted, measurement configurations are optimized, and redundant parameters are eliminated from identification model, calibration accuracy is still limited under measurement noise. This might be because huge gaps still exist among the singular values of typical identification Jacobians, thereby causing the identification models ill conditioned. This paper addresses such problem by using new identification models established in two steps. First, the typical models are divided into the submodels with truncated singular values. In this way, the unknown parameters corresponding to the abnormal singular values are removed, thereby reducing the condition numbers of the new submodels. However, these models might still be ill conditioned. Therefore, the second step is to further centralize the singular values of each submodel by using a matrix balance method. Afterward, all submodels are well conditioned and obtain much higher observability indices compared with those of typical models. Simulation results indicate that significant improvements in the stability of identification results and the identifiability of unknown parameters are acquired by using the new identification submodels. Experimental results indicate that the proposed calibration method increases the identification accuracy without incurring additional hardware setup costs to the typical calibration method.

Cable-driven parallel manipulators (CDPMs) offer advantages over traditional parallel manipulators. Though their ability to accelerate is higher than the traditional motion platforms, the capabilities are often not used optimally. The issues of cable slackening (especially at higher accelerations) and the emergence of singularity poses have traditional limitations. This paper analyzes and generates manipulator configurations that reduce the effect of these two essential hindrances of deploying CDPMs. A methodology, inspired by rigid body dynamics of multiple contact problems, used to optimize the positions of attachment points, is shown to be effective.

With the widespread development of leg exoskeletons to provide external force-based repetitive training for gait rehabilitation, the prospect of undesired movement adaptation due to applied forces and imposed constraints require adequate investigation. A cable-driven leg exoskeleton, CDLE, presents a lightweight, flexible, and redundantly actuated architecture that enables the possibility of system parameters modulation to alter human–robot interaction while applying the desired forces. In this work, multi-joint stiffness performance of CDLE is formulated to systematically analyze human–CDLE interaction. Further, potential alterations in CDLE architecture are presented to tune human–CDLE interaction that favors the desired human leg movement during a gait rehabilitation paradigm.

In this work, a planar cable parallel robot (CPR) driven by four cable-and-pulley differentials is proposed and analyzed. A new cable-and-pulley differential is designed by adding an extra pulley to eliminate the modeling inaccuracies due to the pulley radius and obviate the need of solving the complex model which considers the pulley kinematics. The design parameters of the proposed CPR are determined through multi-objective optimal design for the largest total orientation wrench closure workspace (TOWCW) and the highest global stiffness magnitude index. The proposed differentially driven CPR is evaluated by comparing various performance indices with a fully actuated CPR.

Suppose in a given planar circular region, there are smart mobile evaders and we want to find them using sweeping agents. We assume the sweeping agents are in a line formation whose total length is predetermined. We propose procedures for designing a sweeping process that ensures the successful completion of the task, thereby deriving conditions on the sweeping velocity of the linear formation and its path. Successful completion of the task means that evaders with a given limit on their velocity cannot escape the sweeping agents. We present results on the search time given the initial conditions.

To improve the uniformity of coating thickness and spraying efficiency, new point cloud modeling and slicing algorithm are proposed to deal with free-form surfaces for the spray painting robot in this paper. In the process of point cloud modeling, the edge preservation algorithm is firstly presented to avoid damaging the edge characteristic of the point cloud model. For the spraying gun, the coating deposition model on the free-form surface is determined on the basis of the elliptic double β distribution model. Then, the grid projection algorithm is proposed to obtain grid points between adjacent slices on the free-form surface. Based on this, the analytical solution for calculating the coating thickness at each grid point is obtained. The cross-section contour points are obtained by intercepting the point cloud model with several parallel slices, which is important for the trajectory planning of the spray painting robot. Finally, the uniformity of coating thickness is optimized in terms of the moving speed of the spraying gun and the slice thickness. The simulation and numerical experiment results show that the uniformity of coating thickness and spraying efficiency are improved using the proposed point cloud modeling and slicing algorithm.

This paper deals with the multi-objective optimal design of a novel 6-degree of freedom (DOF) hybrid spray-painting robot. Its kinematic model is obtained by dividing it into serial and parallel parts. The dynamic equation is formulated by virtual work principle. A performance index for evaluating the compactness of robot is presented. Taking compactness, motion/force transmissibility, and energy consumption as performance indices, the optimal geometric parameters of the robot are selected in the Pareto-optimal set by constructing a comprehensive performance index. This paper is very useful for the development of the spray-painting robot.

Effective motion planning and localization are necessary tasks for swarm robotic systems to maintain a desired formation while maneuvering. Herein, we present an inchworm-inspired strategy that addresses both these tasks concurrently using anchor robots. The proposed strategy is novel as, by dynamically and optimally selecting the anchor robots, it allows the swarm to maximize its localization performance while also considering secondary objectives, such as the swarm’s speed. A complementary novel method for swarm localization, that fuses inter-robot proximity measurements and motion commands, is also presented. Numerous simulated and physical experiments are included to illustrate our contributions.

This paper formulates and solves a new problem of global practical inverse optimal exponential path-tracking control of mobile robots driven by Lévy processes with unknown characteristics. The control design is based on a new inverse optimal control design for nonlinear systems driven by Lévy processes and ensures global practical exponential stability almost surely and in the pth moment for the path-tracking errors. Moreover, it minimizes cost function that penalizes tracking errors and control torques without having to solve a Hamilton–Jacobi–Bellman or Hamilton–Jaccobi–Isaacs equation.

For several decades, simulation and analysis of mechanisms have been performed with dedicated computer-aided engineering software that implements general dynamic formulations, known in the literature as multi-body systems (MBS) formulations. The MBS name is related to the structure of the mechanism, which is often considered to be a collection of bodies interconnected by mechanical joints (pairs). Nevertheless, only a few formulations are really based on a true multi-body mechanical model, while many others instantiate mathematically quite different mechanical concepts. This paper aims to identify and discuss the mechanical models that fundament the main multi-body mathematical formulations known in the literature. The main features of each model are outlined, based on a detailed presentation of the structure and equations of motion, together with their link with the kinematic and dynamic formulations. A comparative study related to computational efficiency is then presented for the identified main models, based on a test mechanism. Comparative advantages and disadvantages are discussed at the end, considering the identified mechanical models.