In this article, hybridization of IWD (intelligent water drop) and GA (genetic algorithm) technique is developed and executed in order to obtain global optimal path by replacing local optimal points. Sensors of mobile robots are used for mapping and detecting the environment and obstacles present. The developed technique is tested in MATLAB simulation platform, and experimental analysis is performed in real-time environments to observe the effectiveness of IWD-GA technique. Furthermore, statistical analysis of obtained results is also performed for testing their linearity and normality. A significant improvement of about 13.14% in terms of path length is reported when the proposed technique is tested against other existing techniques.

High-voltage power cables are important channels for power transmission systems. Their special geographical environment and harsh natural environment can lead to many different faults. At present, such special operations in dangerous and harsh environments are performed manually, which not only has high labor intensity and low work efficiency but also has great personal safety risks. In order to solve such difficult problems, this paper studies the power maintenance robot for insulator string replacement, spacer replacement, damper and drainage plate maintenance; the basic configuration and the operation motion planning have been proposed; and the virtual prototype of the inspection maintenance robots has been developed, and then the mechanical structure of the robots has been optimized by the robot kinematics modeling and analyzed the working space based on the Monte Carlo method. The system platform, operation function, structural characteristics and related key technologies involved in the robot system development were systematically summarized; the deep integration point for the robot technology with big data, cloud computing, artificial intelligence, and ubiquitous power Internet-of-Things technologies was also discussed. Finally, the physical prototype of the insulator replacement, drainage plate tightening, and damper replacement operation robot has been developed; several experimental tests on a 220 V live line have been conducted so as to verify the robot engineering practicality; and the main development and future research direction have also been pointed out at last.

This paper addresses the tracking problem for uncertain nonlinear sandwich systems that consist of two nonlinear subsystems and saturation nonlinearity, which is sandwiched between the subsystems. The considered sandwich system is also subject to a nonsymmetric input saturation constraint. Due to the nonsmooth characteristics of sandwiched saturation nonlinearity and also the input saturation function, the design procedure deals with hard challenges. To overcome these difficulties, a recursive approach is suggested that consists of two phases. For the implementation of the proposed approach, a tracking problem is solved in each phase. In the first phase, the second subsystem with sandwiched saturation nonlinearity is considered and the output tracking problem of the desired time-varying reference signal is solved using backstepping method. The outcome of the first phase is the desired reference signal that should be tracked by the first subsystem in the next phase. In the second phase, the robust control input is designed for the first subsystem by employing adaptive sliding mode technique such that, despite the nonsymmetric input saturation constraint, model uncertainty and external disturbances, the output of the first subsystem follows the desired signal that is obtained in the previous phase. The simulation results for a mechanical sandwich system are illustrated to verify the effectiveness of the proposed control method.

Rendering of rigid objects with high stiffness while guaranteeing system stability remains a major and challenging issue in haptics. Being a part of the haptic system, the behavior of human operators, represented as the mechanical impedance of arm, has an inevitable influence on system performance. This paper first verified that the human arm impedance can unconsciously be modified through imposing background forces and resist unstable motions arising from external disturbance forces. Then, a reliable impedance tuning (IT) method for improving the stability and performance of haptic systems is proposed, which tunes human arm impedance by superimposing a position-based background force over the traditional haptic workspace. Moreover, an adaptive IT algorithm, adjusting the maximum background force based on the velocity of the human arm, is proposed to achieve a reasonable trade-off between system stability and transparency. Based on a three-degrees-of-freedom haptic device, maximum achievable stiffness and transparency grading experiments are carried out with 12 subjects, which verify the efficacy and advantage of the proposed method.

The popular approach of assuming a control policy and then finding the largest region of attraction (ROA) (e.g., sum-of-squares optimization) may lead to conservative estimates of the ROA, especially for highly nonlinear systems. We present a sampling-based approach that starts by assuming an ROA and then finds the necessary control policy by performing trajectory optimization on sampled initial conditions. Our method works with black-box models, produces a relatively large ROA, and ensures exponential convergence of the initial conditions to the periodic motion. We demonstrate the approach on a model of hopping and include extensive verification and robustness checks.

An autonomous motion planning framework is proposed, consisting of path planning and trajectory generation. Primarily, a spacious preferred probabilistic roadmap algorithm is utilized to search a safe and short path, considering kinematics and threats from obstacles. Subsequently, a minimum-snap and position-clearance polynomial trajectory problem is transformed into an unconstrained quadratic programming and solved in a two-step optimization. Finally, comparisons with other methods based on statistical simulations are implemented. The results show that the proposed method achieves computational efficiency and a safe trajectory.

In brachytherapy, the manual implantation of seeds is not accurate leading to side effects and limiting the use of new procedures. Robotics solutions have to be fully suitable for medical applications especially considering the operating room. This paper investigates a delta robot solution for improving the accuracy of the prostate brachytherapy procedure by proposing a compact and lightweight robot. In addition, the design was thought as a comanipulated robot for a better acceptability and human–machine interaction. The robot kinematics and singularities were determined and the theoretical capability in term of resolution and force feedback was evaluated. A prototype was built in order to experimentally measure the capability of this first prototype.

This paper proposes a dynamic modeling method of redundant drive spatial parallel mechanism, dynamics of 4-UPS-RPU redundant driving spatial parallel mechanism considering spherical joint clearance are analyzed. The dynamic equation of spherical joint clearance with Lagrange multiplier is built. The influences of single clearance and multiple clearances on dynamic responses of redundant drive spatial parallel mechanisms are analyzed under different clearance values. The results show that the dynamic characteristics of the mechanism with single clearance are basically consistent with the ideal situation, and the dynamic characteristics of the mechanism with multi-clearance are significantly different from the ideal situation.

Robots are now among us and even though they compete with human beings in terms of performance and efficiency, they still fail to meet the challenge of performing a task optimally while providing strict motion safety guarantees. It is therefore necessary that the future generation of robots evolves in this direction. Generally, in robotics state-of-the-art approaches, the trajectory optimization and the motion safety issues have been addressed separately. An important contribution of this paper is to propose a motion planning method intended to simultaneously solve these two problems in a formal way. This motion planner is dubbed PassPMP-PSO. It is based on a periodic process that interleaves planning and execution for a regular update of the environment’s information. At each cycle, PassPMP-PSO computes a safe near-optimal partial trajectory using a new tree encoding technique based on particle swarm optimization (PSO). The performances of the proposed approach are firstly highlighted in simulation environments in the presence of moving objects that travel at high speed with arbitrary trajectories, while dealing with sensors field-of-view limits and occlusions. The PassPMP-PSO algorithm is tested for different tree expansions going from 13 to more than 200 nodes. The results show that for a population between 20 and 100 particles, the frequency of obtaining optimal trajectory is 100% with a rapid convergence of the algorithm to this solution. Furthermore, an experiment-based comparison demonstrates the performances of PassPMP-PSO over two other motion planning methods (the PassPMP, a previous variant of PassPMP-PSO, and the input space sampling). Finally, PassPMP-PSO algorithm is assessed through experimental tests performed on a real robotic platform using robot operating system in order to confirm simulation results and to prove its efficiency in real experiments.

We have introduced a new low-Reynolds-number microrobot with high 3D maneuverability. Our novel proposed microrobot has a higher rank of the controllability matrix with respect to the previous microswimmers which makes it capable of performing complex motions in space. In this study, governing equations of the microswimmer’s motion have been derived and simulated. Subsequently, we have proposed a cascade optimal control technique to control the swimmer trajectory. In the proposed control scheme, the actuation is provided in a way that an exponential stability on the system trajectory error as well as minimum fluctuations of control signals are achieved.

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.

A 3-RRPRR variable spherical symmetrical parallel mechanism (PM) with arc-shaped sliding pairs and no parasitic motion is presented, exhibiting two rotational and one translational (2R1T) degrees of freedom. Three limbs are symmetrically distributed between the base and end-effector; upper and lower parts of each limb are mirror symmetrical around the middle. The geometry, mobility, forward/inverse kinematics, workspace, and parasitic motion of the mechanism are analyzed, showing its ability to achieve large rotations around a continuous rotation axis. Finally, a structure synthesis strategy for variable spherical symmetrical PM is proposed, and several limb types meeting the conditions are obtained.

In this paper, a weighted-neighbor-based cooperation control of multi-quadrotor systems is investigated. A formation tracking problem is treated, where the reference formation trajectory (RFT) is not given a priori. The RFT is only available to some of the quadrotors (i.e. the leaders). In order to attain the fast convergence of the agents, we propose an algorithm to calculate the neighbors’ weights in decentralized way. Then, the weights are used to compose the formation controller. Compared to the widely used average-neighbor-based control method, the proposed control protocol can increase the convergence speed of the cooperation error. Since the formation control is improved in topological scale, the utilization of the proposed algorithms can be extended on any multi-robot systems. We show the improvement of the proposed control protocol by theoretical proof, simulation, and real-time experiments.

Control algorithms of many Degrees-of-Freedom (DOFs) systems based on Inverse Kinematics (IK) or Inverse Dynamics (ID) approaches are two well-known topics of research in robotics. The large number of DOFs allows the design of many concurrent tasks arranged in priorities, that can be solved either at kinematic or dynamic level. This paper investigates the effects of modeling errors in operational space control algorithms with respect to uncertainties affecting knowledge of the dynamic parameters. The effects on the null-space projections and the sources of steady-state errors are investigated. Numerical simulations with on-purpose injected errors are used to validate the thoughts.

An improved FastSLAM based on the robust square-root cubature Kalman filter (RSRCKF) with partial genetic resampling is proposed in this paper. In the proposed method, RSRCKF is used to design the proposal distribution of FastSLAM and to estimate environment landmarks. The proposed method does not require a priori knowledge of the noise statistics. In addition, to increase diversity, it uses the genetic operators-based strategy to further improve the particle diversity. In fact, a partial genetic resampling operation is carried out to maintain the diversity of particles. The proposed method is compared with other methods via simulation and experimental data. It can be seen from the results that the proposed method provides significantly more accurate and robust estimation results compared with other methods even with fewer particles and unknown a priori. In addition, the consistency of the proposed method is better than that of other methods.

In this research, a dynamic model is first established based on screw theory and the principle of virtual work for a bilaterally symmetrical hybrid robot. By combining a novel composite error (NCE) with second-order nonsingular fast terminal sliding mode (SONFTSM) control method, a NCE-based SONFTSM dynamic control method is further presented to guarantee better trajectory tracking performance and synchronization performance simultaneously. The asymptotic convergence of proposed errors and the stability of the proposed control method have been proved theoretically. Finally, the simulation and experiment are implemented to validate the effectiveness of the proposed control method.

The problem of finite-time tracking control for n-link flexible-joint robot manipulators is addressed. An adaptive fuzzy finite-time command-filtered backstepping control scheme is presented to solve the following problems: “explosion of terms” problem, finite-time stabilization of the closed-loop system, and the reduction of computational cost. To this end, new virtual adaptive control signals and new finite-time error compensation mechanism are constructed using inherent properties of robot manipulator systems. Based on the Lyapunov theory, the finite-time stabilization of the closed-loop system is proved. Simulation studies show the effectiveness of the proposed method.

Aiming at 3SPS+1PS parallel hip joint simulator, the maximum stress of branched chains under the suggested trajectory is obtained by elastodynamic analysis. Based on Corten-Dolan fatigue damage theory and Rain-flow counting method, the dynamic stress of each branched chain is statistically analyzed. The fatigue life prediction shows that branched-chain A2P2C2 is the weakest component for the simulator. Finally, the fatigue reliability is analyzed and the fatigue life and reliability under different structural parameters are discussed. The study shows that the fatigue life of each branched chain can be increased or balanced by increasing structural parameters or exchanging initial motion parameters.

This paper emphasizes on Bacterial Foraging Optimization Algorithm for effective and efficient navigation of humanoid NAO, which uses the foraging quality of bacteria Escherichia coli for getting shortest path between two locations in minimum time. The Gaussian cost function assigned to both attractant and repellent profile of bacterium performs a major role in obtaining the best path between any two locations. Mathematical formulations have been performed to design the control architecture for humanoid navigation using the proposed methodology. The developed approach has been tested in a simulation platform, and the simulation results have been validated in an experimental platform. Here, motion planning for both single and multiple humanoid robots on a common platform has been performed by integrating a petri-net architecture for multiple humanoid navigation. Finally, the results obtained from both the platforms are compared in terms of suitable navigational parameters, and proper agreements have been observed with minimal amount of error limits.

The search space of the path planning problem can greatly affect the running time and memory consumption, for example, the concave obstacle in grid-based map usually leads to the invalid search space. In this paper, the filling container algorithm is proposed to alleviate the concave area problem in 2D map space, which is inspired from the scenario of pouring water into a cup. With this method, concave areas can be largely excluded by scanning the map repeatedly. And the effectiveness has been proved in our experiments.