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.

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.

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.

A method for the time suboptimal control of an industrial manipulator that moves along a specified path while keeping its end-effector orientation unchanged is proposed. Nonlinear system equations that describe the manipulator motion are linearized at each time step along the path. A method which gives control inputs (joint angular velocities) for time suboptimal control of the manipulator is developed. In the formulation, joint angular velocity and acceleration limitations are also taken into consideration. A six degree of freedom elbow type manipulator is used in a case study to verify the method developed.

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.

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.

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 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.

We proposed a compliant leg configuration that enhances the conventional pantograph design with leaf springs. The following facts characterize the proposed configuration: (1) Due to the use of the pantograph structure, the mass is centralized around the hip joint, reducing the lower leg inertia; (2) Leaf springs are chosen as elastic parts to increase energy efficiency and estimate foot-end contact forces. Compared with coil springs, leaf springs require no guide rails to deploy, and their stiffness can be easily adjusted through shape cutting. Analytical models are introduced to analyze the leg’s stiffness and estimate the contact forces only with the deflections of leaf springs. A one-leg robot based on the proposed design is built, and various experiments are conducted. Experiments regarding the stiffness calibration and the contact forces estimation showed an acceptable agreement with the analytical model. Experiments of dropping demonstrate the feasibility of the leg to perform spring-like behaviors. Experiments of periodic hopping demonstrate the feasibility of using spring deflections to detect touch-down events. For energy efficiency, it is also observed that the elastic leg has a 20% increment concerning the jumping height in the flight phase, compared with the one where leaf springs are replaced with rigid materials.

This paper deals with the problem of collision course checking in a dynamic environment for mobile robotics applications. Our method is based on the relative kinematic equations between moving objects. These kinematic equations are written under polar form. A transformation of coordinates is derived. Under this transformation, collision between two moving objects is reduced to collision between a stationary object and a virtual moving object. In addition to the direct collision course, we define the indirect collision course, which is more critical and difficult to detect. Under this formulation, the collision course problem is simplified, and complex scenarios are reduced to simple scenarios. In three-dimensional (3D) settings, the working space is decomposed into two planes: the horizontal plane and the vertical plane. The collision course detection in 3D is studied in the vertical and horizontal planes using 2D techniques. This formulation brings important simplifications to the collision course detection problem even in the most critical and difficult scenarios. An extensive simulation is used to illustrate the method in 2D and 3D working spaces.

In this study, we present a new approach to improving vocal fold access to perform phonomicrosurgery. It is done by shooting the laser through a mirror to reach the vocal fold hidden parts. A geometrical study of laser shooting path was conducted for vocal fold anatomical constraints, followed by devising a laser-shooting system conceptual design. Control laws were developed and tested by simulation and validated experimentally on a test bench in a monocular and stereoscopic configuration. Simulation and experimental results are provided to demonstrate the effectiveness of the developed approach.

Dynamic simulations of the cable-driven parallel robots (CDPRs) with cable models closer to reality can predict the motions of moving platforms more accurately than those with idealisations. Hence, the present work proposes an efficient and modular computational framework for this purpose. The primary focus is on the developments required in the context of CDPRs actuated by moving the exit points of cables while the lengths are held constant. Subsequently, the framework is extended to those cases where simultaneous changes in the lengths of cables are employed. Also, the effects due to the inertia, stiffness and damping properties of the cables undergoing 3D motions are included in their dynamic models. The efficient recursive forward dynamics algorithms from the prior works are utilised to minimise the computational effort. Finally, the efficacy of the proposed framework and the need for such an inclusive dynamic model are illustrated by applying it to different application scenarios using the spatial $4$-$4$ CDPR as an example.

The accurate modelling of robot dynamics is essential for the design of model-based robot controllers. However, dynamic models have very complicated features which can be attributed to several reasons. For example, the continuously-varying arm configuration, uncertain effects of load handling on the dynamic stability of the arm, and the high degree of non-linearity and coupling exhibited between the different links. Hence, the accurate modelling of these effects will play an important role in the design of robust controllers. Towards this end, an efficient and fast method for the on-line tuning of robot dynamic parameters must be devised. This work proposes to solve this problem as follows. First, a simplified dynamic model of the robot is developed. The model allows for direct and straightforward extraction and regrouping of dynamic parameters. The resulting dynamic parameters are formulated as a regression equation which is linear in the dynamic parameters. Finally, the algorithm is executed using a Transputer development system to speed up the computation and meet real-time constraints. The efficiency of the approach is demonstrated by a case study.

Some changes have uncomfortable characteristics. Change is inevitable, large, penetrating, unpredictable. There is thus the need to create ‘learning’ organisations capable of coping with change. The following topics are considered:

1. Changes in organisational shape – transition from hierarchical triangular shaped to ‘heterarchical’ diamond shaped organisations – the breakdown hierarchy.

2. Changes in the role of people in manufacturing and services including the public service.

3. ‘Managers’ and new technology – management role enhanced co-ordinating and creating motivation.

4. Three models for change.

5. The productivity of automation is essential. ‘Working’ years are shortening, ‘dependent’ years are lengthening.

6. People as assets.

7. Technology, Human Aspects, Process of change = TRAP.

This is a concise survey of the activities carried out by the Robotics Laboratory of the “J. Stefan” Institute, University of E. Kardelj, Ljubljana (Yugoslavia) on the field of robotics research and development of robots. A list of research themes is given with a brief explanation of each containing the objectives, the obtained results, the history and the future outlook. Besides, the main projects concerned with the development of industrial robots are described, as well as the equipment which enables practical work and experimentations as a major element of the laboratory research and educational activities.

This paper focuses on developing a planning strategy for robotic assembly. At first, channel and junction are defined by using half-spaces, and free-space inside the female part is approximately decomposed by channels and junctions. Then, a simple and efficient algorithm to find the assembly path of the male part is developed, in which any path between the shortest and safest paths can be easily found by just changing the clearance gap between the male and female parts. Next, the robot arm is considered in the path planning, in which a feasible grasp angle region is obtained to avoid a collision between the robot arm and the female part during the assembly process. An optimum grasping angle can be found in the feasible grasping angle region by applying a proper performance index. Finally, a simple robotic assembly using the algorithm is numerically demonstrated.

In this paper a control strategy for a redundant PUMA robot is presented. This robot is obtained from the conventional PUMA robot by addition of a joint parallel to the elbow joint. For redundancy resolution the following approach is chosen. From the position and pointing direction of the end effector of the PUMA robot the position and orientation of the fourth link of a 4R-manipulato? is calculated and the redundancy is resolved for this manipulator. This is done by adding an equation to the relationship between the joint angles and position and orientation of the fourth link. By this approach a control strategy is derived that allows motions of the end effector of the PUMA robot in a large part of its work space and shows repeatable behaviour. Furthermore, the redundancy is utilized so that the fiexture of the wrist is kept small.