Construction is of great interest in the application of practical and theoretical results in the field of robotics. The economic efficiency potential of using robots is defined by construction quantities, a high level of manual work, and hard and unfavorable working conditions. Mounting and finishing operations are the main focus for the practical use of robots. This paper describes technological characteristics of such operations, suggests kinematic structures for mounting and finishing operations, and provides kinematic model designs as examples. Taking into consideration the management details of mounting and finishing operations, this paper also makes recommendations on movement planning and on the formation of the laws of drive control. In the conclusion, recommendations on applying the results and using computer technologies in the development of control programs are presented.

This paper presents the teleoperation of a parallel robot based on the Stewart–Gough platform. The robot is an experimental prototype capable of sliding along electrical lines in order to carry out different inspection and maintenance tasks. The paper also describes the kinematic equations of the parallel robot and their solution. The teleoperation of the prototype took place in a testing bank developed in the laboratory and containing the basic elements of electrical lines. The operator who performs the task uses a six degrees-of-freedom master-arm with force reflection, which also has an image-viewing system providing the operator with stereoscopic vision and allowing him/her to calibrate the information of the local station simulator with the real environment through the blending of images. The paper also presents the results of the laboratory experiments of the robot sliding along a line.

As a heavy load is applied to the parallel manipulators, it causes inaccuracies while positioning the end-effector or unbalanced dynamic forces in the legs. Various load-balancing techniques overcome this. However, the disadvantage of most load-balancing mechanisms is that they add inertia to the assembly and decrease the speed of motion. This article studies a new load-balancing method (a passive damper mechanism). The passive balancing mechanism is proposed to negate the inertia effects while countering the static inaccuracies in the parallel mechanism. This is verified by the structural analysis of the mechanism. The impact of the damper element on the dynamics of the mechanism is unknown. Hence, a complete mathematical model for the balancing mechanism has been developed to study its impact on the dynamics of the entire structure. Laplace transformations characterize the system response. The inclusion of a passive damper in a 3-prismatic-prismatic-revolute-spherical system was examined and found to be stable and critically damped. Such a passive damper was envisaged to facilitate additional force transmission for the actuators, and the DC gain from the system response validates the torque support for the actuators.

Visual simultaneous localization and mapping (VSLAM) is a relevant solution for vehicle localization and mapping environments. However, it is computationally expensive because it demands large computational effort, making it a non-real-time solution. The VSLAM systems that employ geometric reconstructions are based on the parallel processing paradigm developed in the Parallel Tracking and Mapping (PTAM) algorithm. This type of system was created for processors that have exactly two cores. The various SLAM methods based on the PTAM were also not designed to scale to all the cores of modern processors nor to function as a distributed system. Therefore, we propose a modification to the pipeline for the execution of well-known VSLAM systems so that they can be scaled to all available processors during execution, thereby increasing their performance in terms of processing time. We explain the principles behind this modification via a study of the threads in the SLAM systems based on PTAM. We validate our results with experiments describing the behavior of the original ORB-SLAM system and the modified version.

In a gait generation method based on the parametric excitation principle, appropriate motion of the center of mass restores kinetic energy lost by heel strike. The motion is realized by bending and stretching a swing-leg regardless of bending direction. In this paper, we first show that inverse bending restores more mechanical energy than forward bending, and then propose a parametric excitation-based inverse bending gait for a kneed biped robot, which improves gait efficiency of parametric excitation walking.

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.

Underwater Modular Self-Reconfigurable (UMSR) robots, made up of many identical modules, can adjust their configurations to multiple underwater environments or tasks. They can be used in many complex underwater occasions where the ROVs/AUVs can't work well. However, their reconfiguration is difficult because this has to involve many connection adding and removing operations which are difficult to be executed in the underwater environment. To reduce the times of these operations, we propose the theory of Topological Transformation (TT), which includes some definitions in TT, the basic approach to TT, and the Genetic Algorithm (GA) based solution for the optimal TT.

This paper provides a mathematical approach to study the duration of collision-free motion of multiple unmanned autonomous vehicles (UXVs) operating in confined areas. A simple geometric model of the UXVs is first proposed, and the dynamics of the model is shown. The expected time of first collision is then formulated using the concept of mean free path from molecular dynamics. Monte-Carlo simulation is performed to verify the theory developed. The expected time of first collision is a function of the number of UXVs, the UXV speed and the sensor field of view (FOV) for a given operational area and vehicle size. Furthermore, the critical number of UXVs, above which collision can be deemed to occur instantly, is obtained.

Exploration is a fundamental problem in robotics, and multi-robot systems exploration has been extensively studied in this field. In order to overcome the problem of a non-optimal target being selected in the exploration process, a revised single linkage clustering frontier cell (CFC) algorithm is proposed to calculate the exploration benefit of all available frontier cells. Moreover, there exist unexplored islands for most of the bidding-based multi-robot coordination algorithms in the exploration of unknown environments. To deal with this problem, some rules switched by emotion states are proposed. So, the proposed bidding coordination algorithm with CFC and an emotion switch has a hierarchical architecture. The upper level is modeled as an automaton, which is used to represent emotion status, and the emotion variables decide whether a robot will participate in a bid and explore an unknown area abiding by the walking rules. In the lower level, the robots perform bidding activities with CFC and the walking rules according to the emotion variables. We tested and evaluated our approach by means of experiments both in a simulated environment and with real robots. The experiments results demonstrate that the exploration efficiency is improved, and our algorithm has a greater coverage rate than classic bidding-based coordination algorithms.

The Stewart platform manipulator is a fully kinematic linkage system that has major mechanical differences from typical serial link robots. It is a six-axis parallel robot manipulator with a high force-to-weight ratio and good positioning accuracy that exceeds that of a conventional serial link robot arm. This study examines the dynamic equations and control methodology for a Stewart platform. Because manual symbolic expansion of Stewart platform robot dynamic equations is tedious, time-consuming, and prone to errors, an automated derivation process is highly desired. The main goal of this work is to present an efficient procedure for computer generation of dynamic equations for a Stewart platform manipulator. As MATLAB has a powerful signal processing toolbox along with symbolic processing capabilities and is widely used as a common technical computing environment in many universities and research laboratories, the objective of this study was to develop a MATLAB-based approach for symbolic computation for a parallel linked robot. Additionally, a computed-torque control methodology is utilized for such a structure. Simulation results demonstrate the effectiveness of the proposed control methodology.

A novel approach to estimate the real-time moving trajectory of an object is proposed in this paper. The object's position is obtained from the image data of a charge coupled device (CCD) camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Kalman filter and neural networks are utilized cooperatively. Since the Kalman filter needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach, the Kohonen networks, which have a high adaptability to the memory of the input–output relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of a self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the extended Kalman filter is demonstrated through real experiments.

A number of techniques, grouped under the umbrella term of usability inspection, have been devised in recent years to help software developers focus more closely on the needs of end-users during the development of interactive applications. Central to the use of such methods is the question of how proposed designs can be tested before a complete system has been implemented. This paper discusses the role of high and low-fidelity prototypes used for this purpose in software development and proposes the use of a “variable-fidelity” prototype as an aid to the development of interactive robotic systems. The approach is outlined and illustrated through the example application of an Interactive Robotic Visual Inspection System (IRVIS) developed for use by a person with limited physical manipulation skills.

In order to achieve high efficient self-motion for a redundant robot manipulator, a novel quadratic programming and varying-gain recurrent neural network based varying-gain neural self-motion (VGN-SM) approach is proposed and developed. With VGN-SM, the convergence errors can be adaptively and efficiently converged to zero. For comparisons, a traditional fixed-parameter neural self-motion (FPN-SM) approach is also presented. Theoretical analysis shows that the proposed VGN-SM has higher accuracy than the traditional FPN-SM. Finally, comparative experiments between VGN-SM and FPN-SM are performed on a six degrees-of-freedom robot manipulator to verify the advantages of the novel VGN-SM.

In this paper, we propose an approach for computing suboptimal grasps of polyhedral objects. Assuming n hard-finger contact with Coulomb friction model and based on central axes of the grasp wrench, we develop a new necessary and sufficient condition for n-finger grasps to achieve force-closure property. Accordingly, we reformulate the proposed force-closure test as a new linear programming problem, which we solve using an interior point method. Furthermore, we present an approach for finding appropriate stable grasps for a robotic hand on arbitrary objects. We use the simulated annealing technique for synthesizing suboptimal grasps of 3D objects. Through numerical simulations on arbitrary shaped objects, we show that the proposed approach is able to compute good grasps for multifingered hands within a reasonable computational time.

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.

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.

This paper proposes an approach for the high-level programming of co-designed robots that reduces programming complexity. Particularly, the work presented focuses on the programming framework of an intelligent system, based on the IEEE Standard Ontologies for Robotics and Automation, which allows users the automatic design of robots and the automatic implementation of controllers in the Robot Operating System (ROS). In our approach, the co-designed robot functionalities are automatically translated into visual programming blocks allowing non-expert users an easy robot programming by means of a visual programming language. Several robot configurations and three case studies are provided as a proof of concept. The validation, in terms of usability, of the framework has been carried out with inexperienced users showing promising results.

Cellular automata can model the information processing aspects of a self-replicating programmable constructing system (SRPC), but these models do not contain any notion of material parts and are poor at modelling features of a system that depend upon the motion and connectivity of its components. Physical systems with thousands of parts have the disadvantage that they are time consuming to develop. To overcome these limitations, a simulation environment is presented at a level of abstraction that models motion and connectivity. An SRPC which takes a disorganised collection of parts as its input has been implemented in this environment.