Recently, there has been a lot of interest concerning remote-controlled robot manipulation in hazardous environments including construction sites, national defense areas, and disaster areas. However, there are problems involving the method of remote control in unstructured work environments such as construction sites. In a previous study, to address these problems, a multipurpose field robot (MFR) system was described. Though the case studies on construction, to which “MFR for installing construction materials” was applied, however, we found some factors to be improved. In this paper, we introduce a prototype of improved multipurpose field robot (IMFR) for construction work. This prototype robot helps a human operator easily install construction materials in remote sites through an upgraded additional module. This module consists of a force feedback joystick and a monitoring device. The human–robot interaction and bilateral communication for strategic control is also described. To evaluate the proposed IMFR, the installation of construction materials was simulated. We simulated the process of installing construction materials, in this case a glass panel. The IMFR was expected to do more accurate work, safely, at construction sites as well as at environmentally hazardous areas that are difficult for humans to approach.

Maximum load carrying capacity (MLCC) of flexible robot manipulators is computed based on closed-loop approach. In open-loop approach, controller is not considered, so the end effector deviation from the predefined path is significant and the accuracy constraint restrains the maximum payload before actuators go into saturation mode. In order to improve the MLCC, a method based on closed-loop strategy is presented. Since in this case the accuracy is improved the actuators constraint is not a major concern and full power of actuators can be used. Since controller can play an important role in improving the maximum payload, a sliding mode based partial feedback linearization controller is designed. Furthermore, a fuzzy variable layer is used in sliding mode design to boost the performance of the controller. However, the control strategy required measurements of elastic variables velocity that are not conveniently measurable. So a nonlinear observer is designed to estimate these variables. Stability analysis of the proposed controller and state observer are performed on the basis of Lyapunov's direct method. In order to verify the effectiveness of the presented method, simulation is done for a two-link flexible manipulator. The obtained maximum payload in open-loop and closed-loop cases is compared and the superiority of the method is illustrated and the results are discussed.

In this work, we propose an output feedback sliding mode control (SMC) method for trajectory tracking of robotic manipulators. The design process has two steps. First, we design a stable SMC controller by assuming that all state variables are available. Then, an output feedback version of this SMC design is presented, which incorporates a model-free linear observer to estimate unknown velocity signals. We then show that the tracking performance under the output feedback design can asymptotically converge to the performance achieved under state-feedback-based SMC design. A detailed stability analysis is given, which shows semi-global uniform ultimate boundedness property of all the closed-loop signals. The proposed method is implemented and evaluated on a robotic system to illustrate the effectiveness of the theoretical development.

The workspace of a robotic manipulator is a very important issue and design criteria in the context of optimum design of robots, especially for parallel manipulators. Though, considerable research has been paid to the investigations of the three-dimensional (3D) constant orientation workspace or position workspace of parallel manipulators, very few works exist on the topic of the 3D orientation workspace, especially the nonsingular orientation workspace and practical orientation workspace. This paper addresses the orientation workspace analysis of a special class of the Stewart–Gough parallel manipulators in which the moving and base platforms are two similar semisymmetrical hexagons. Based on the half-angle transformation, a polynomial expression of 13 degree that represents the orientation singularity locus of this special class of the Stewart–Gough parallel manipulators at a fixed position is derived and graphical representations of the orientation singularity locus of this special class of the Stewart–Gough manipulators are illustrated with examples to demonstrate the result. Exploiting this half-angle transformation and the inverse kinematics solution of this special class of the Stewart–Gough parallel manipulators, a discretization method is proposed for computing the orientation workspace of this special class of the Stewart–Gough parallel manipulators taking limitations of active and passive joints and the link interference all into consideration. Based on this algorithm, this paper also presents a new discretization method for computing the nonsingular orientation workspace of this class of the manipulators, which not only can satisfy all the kinematics demand of this class of the manipulators but also can guarantee the manipulator is nonsingular in the whole orientation workspace, and the practical orientation workspace of this class of the manipulators, which not only can guarantee the manipulator is nonsingular and will never encounter any kinematic interference but also can satisfy the demand of the orientation workspace with a regular shape in practical application, respectively. Examples of a 6/6-SPS Stewart–Gough parallel manipulator of this special class are given to demonstrate these theoretical results.

Recently, satellite images of most urban settings has become available on the internet. In this study, a novel mapping and global localization approach, which uses these images, is proposed for outdoor mobile robots operating in urban environment. The mapping of large-scale outdoor environments is done by employing the satellite images acquired by remote sensing technology, and then a map-based approach, that is, Monte Carlo localization is used for localization. The novelty of proposed method is that it uses standard equipment present on almost all autonomous robots and satellite images thus it acts as an alternative to GPS data in urban environments. Extensive field tests are presented to demonstrate the effectiveness of proposed approach.

In nature, sounds from multiple sources, as well as reflections from the surfaces of the physical surroundings, arrive concurrently from different directions at the ears of a listener. Despite the fact that all of these waveforms sum at the eardrums, humans with normal hearing can effortlessly segregate interesting sounds from echoes and other sources of background noises. This paper presents a two-microphone technique for localization of sound sources to effectively guide robotic navigation. Its fundamental structure is adopted from a binaural signal-processing scheme employed in biological systems for the localization of sources using interaural time differences (ITDs). The two input signals are analyzed for coincidences along left/right-channel delay-line pairs. The coincidence time instants are presented as a function of the interaural coherence (IC). Specifically, we build a sphere head model for the selected robot and apply the mechanism of binaural cues selection observed in mammalian hearing system to mitigate the effects of sound echoes. The sound source is found by determining the azimuth at which the maximum of probability density function (PDF) of ITD cues occurs. This eliminates the localization artifacts found during tests. The experimental results of a systematic evaluation demonstrate the superior performance of the proposed method.

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.

It is difficult to design controllers for the complicated dynamics of omnidirectional vehicles steered by multiple wheels with distributed traction force. In this paper, the dynamic model of a three-wheel omnidirectional vehicle, which is linearized to simplify controller design, is developed. The conditions of making its dynamics linear are derived first. Then, a strategy of planning wheel velocities to satisfy these conditions is proposed. Consequently, three-wheel omnidirectional vehicle can be easily treated by classical linear control theories. Finally, a linear optimal tracker is designed to control the omnidirectional vehicle for desired movement trajectories. In particular, the dynamic model includes the motors installed in the three-wheel omnidirectional vehicle, making it a practical model. Three kinds of vehicle trajectories illustrate the planning of wheel trajectories for linearizing the vehicle dynamics, and simulations demonstrate the performance of the linear optimal tracker. In addition, experimental results of a practical three-wheel omnidirectional vehicle are also included.

A hydraulic flexible joint inspired by the actuation system of spiders is investigated in this paper. Its design and characteristics are discussed and a mathematical model is developed to describe its static behaviour. Results of experimental tests are presented to validate its performance. A comparison to other hydraulic actuation systems is performed. The use of the proposed hydraulic flexible joint in adaptive robotic structures is addressed and discussed.

Sound source tracking is an important function for autonomous robots, because sound is omni-directional and can be recognized in dark environment. This paper presents a new approach to sound source tracking for mobile robots using auditory sensors. We consider a general type of two-wheeled mobile robot that has wide industrial applications. Because obstacle avoidance is also an indispensable function for autonomous mobile robots, the robot is equipped with distance sensors to detect obstacles in real time. To deal with the robot's nonholonomic constraint and combine information from the auditory and distance sensors, we propose a model reference control approach in which the robot follows a desired trajectory generated by a reference model. The effectiveness of the proposed method is confirmed by experiments in which the robot is expected to approach a sound source while avoiding obstacles.

A CCC limb and a new 3CCC parallel mechanism have been designed in this paper based on geometry analysis. Their mobility and geometrical constraints are discussed by using screw theory and geometrical equations separately. Following that both the inverse and forward kinematics of the 3CCC parallel mechanism are proposed, in which Dixon's resultant is used to get the forward solutions for the orientation and a eighth-order polynomial equation in one unknown is obtained, leading to the results for the position analysis, numerical examples confirm these theoretical results. A short comparison with the traditional Stewart platforms is presented in terms of kinematics, workspace and trajectory planning.

Tendon sheath actuation is found in many applications, particularly in robotic hands and surgical robots. Due to the friction between the tendon and sheath, many undesirable characteristic such as backlash, hysteresis and non-linearity are present. It is desirable to know the end-effector force and elongation of the tendon to control the system effectively, but it is not always feasible to fix sensors at the end effector. A method to estimate the end-effector parameters using only a force and position sensor at the proximal site is given. An analytical study is presented and experiments are reported to support the result, showing a maximum full-scale error of approximately 7%. This result is achieved if the shape of the sheath remains the same and buckling is negligible. The results presented in this study could contribute towards haptic development in robotics surgery.

In this paper, the combination of neural network (NN), proportional derivative (PD), and robust controller are used for determining the maximum load-carrying capacity (MLCC) of articulated robots, subject to both actuator and end-effector deflection constraints. The proposed technique is then applied to articulated robots, and MLCC is obtained for a given trajectory. In the practical simulations, it's impossible to determine the parameters of robot model exactly, so the trajectory tracking performance of the proportional integral derivative (PID) and computed torque methods significantly decrease. The PD control of robot has major problem, it cannot guarantee zero steady state error. For this reason, the NN controller with PD and robust controller are used. The multilayer neural network is also used to compensate gravity and friction effects. By using Lyapunov Direct Method it is shown that the stability of closed loop system would be guaranteed, if the weights of multilayer had certain learning rules. Standard back propagation algorithm is used as a learning algorithm to update the connection weights of the NN controller. The simulation results of the proposed adaptive robust neural network (ARNN) controller are compred with sliding mode and feedback linearization methods for flexible joint robot, and compared with open loop controller for 3D industrial robot. The obtained results assured the robustness and improvement in MLCC in the presence of uncertainties in dynamic model of the robot arm and external disturbances. In fact, adaptive robust NN controller suppresses disturbances accurately and achieves very small errors between commanded and actual trajectories.