Many object surfaces involve a number of pieces, expressed by different equations. Previous methods of optimal grasp planning can hardly cope with such cases. Ding et al. solve this problem by characterizing the object surface with convex facets and discrete points, then selecting the eligible ones for force-closure, and finally seeking the optimal contact positions on the selected elements. So far, however, no point contact with friction (PCwF) but only frictionless point contacts (FPC) can be used on the facets, while soft finger contacts (SFC) are excluded at all. In this paper, to the above two surface elements we add line segments. Moreover, the limitations on the contact types are completely removed. A general condition and a quantitative criterion of eligibility are presented, followed by a heuristic algorithm and an iterative algorithm for finding the better eligible elements. Three common examples show: the new advances make the formerly tough problems smoothly solvable.

The problem of wheeled mobile robot (WMR) navigation toward an unknown target in a cluttered environment has been considered. The biologically inspired navigation algorithm is the equiangular navigation guidance (ENG) law combined with a local obstacle avoidance technique. The collision avoidance technique uses a system of active sensors which provides the necessary information about obstacles in the vicinity of the robot. In order for the robot to avoid collision and bypass the enroute obstacles, the angle between the instantaneous moving direction of the robot and a reference point on the surface of the obstacle is kept constant. The performance of the navigation strategy is confirmed with computer simulations and experiments with ActivMedia Pioneer 3-DX wheeled robot.

Surgical robotics is the study and application of advanced robotic technology to diverse surgical procedures, particularly to minimally invasive surgery. The advanced robotic technology in minimally invasive surgery leads to momentous change in and generates a tremendous impact on surgery, resulting in less pain and scarring, reduced blood loss and transfusions, lower risk of complication, shorter hospital stays and faster recovery periods.

This work describes a systematic methodology for the synthesis of tendon-driven manipulators. A method for enumerating the topology of tendon routings is first established. To conform with the enumerated structures, the kinematic synthesis of the manipulator using singular value decomposition is then developed. Design equations for synthesizing a general tendon-driven manipulator with isotropic transmission characteristics are subsequently derived. It is shown that the design methodology may give designers wider selection in determining the tendon routing topology than prior methods by other literature.

In this paper, a decoupled offline path planning approach for determining the collision-free path of end effectors of multiple robots involved in coordinated manipulation is proposed. The proposed approach for decoupled path planning is a two-phase approach in which the path for coordinated manipulation is generated with a coupled interaction between collision checking and path planning techniques. Collision checking is done by modelling the links and environment of robot using swept sphere volume technique and utilizing minimum distance heuristic for interference check. While determining the path of the end effector of robots involved in coordinated manipulation, the obstacles present in the workspace are considered as static obstacles and the links of the robots are viewed as dynamic obstacles by the other robot. Coordination is done in offline mode by implementing replanning strategy which adopts incremental A* algorithm for searching the collision-free path. The effectiveness of proposed decoupled approach is demonstrated by considering two examples having multiple six degrees of freedom robots operating in 3D work cell environment with certain static obstacles.

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.

This paper deals with the design and implementation of a visual kinematic control scheme for a redundant manipulator. The inverse kinematic map for a redundant manipulator is a one-to-many relation problem; i.e. for each Cartesian position, multiple joint angle vectors are associated. When this inverse kinematic relation is learnt using existing learning schemes, a single inverse kinematic solution is achieved, although the manipulator is redundant. Thus a new redundancy preserving network based on the self-organizing map (SOM) has been proposed to learn the one-to-many relation using sub-clustering in joint angle space. The SOM network resolves redundancy using three criteria, namely lazy arm movement, minimum angle norm and minimum condition number of image Jacobian matrix. The proposed scheme is able to guide the manipulator end-effector towards the desired target within 1-mm positioning accuracy without exceeding physical joint angle limits. A new concept of neighbourhood has been introduced to enable the manipulator to follow any continuous trajectory. The proposed scheme has been implemented on a seven-degree-of-freedom (7DOF) PowerCube robot manipulator successfully with visual position feedback only. The positioning accuracy of the redundant manipulator using the proposed scheme outperforms existing SOM-based algorithms.

Model-based advanced control approaches are needed to achieve high speed and acceleration and precision in robotic operations. These control schemes need a proper dynamic model. Many approaches have been proposed by different authors in order to obtain the dynamic model of these structures. However, most of them do not consider the possibility to introduce redundant sensor data. In this paper, a methodology for obtaining a compact dynamic model considering passive joint sensor data is proposed. The dynamic model is defined in compact and structured form, which makes it appropriate to be used in advanced control techniques.

This paper proposes a control scheme for the teleoperation of a mobile robot in presence of time delay. Our proposal uses a compensation of the time delay based on a human operator's model and a simple 3D augmented reality scheme; both are related through a prediction system. Unlike other strategies, the proposed scheme has a model of the human operator inside it, including his decision so that human and robot “push in the same direction.” The stability of the teleoperation system adding the proposed control scheme is proven concluding how the time delay changes the convergence rate and the convergence ball size. Finally, to illustrate the performance and stability of the proposed control structure, several teleoperation experiments in presence of various delays are shown.

A brief history of robotic surgery is provided, which describes the transition from autonomous robots to hands-on systems that are under the direct control of the surgeon. An example of the latter is the Acrobot (for active-constraint robot) system used in orthopaedics, whilst soft-tissue surgery is illustrated by the daVinci telemanipulator system. Non-technological aspects of robotic surgery have often been a major impediment to their widespread clinical use. These are discussed in detail, together with the role of navigation systems, which are considered a major competitor to surgical robots. A detailed description is then given of a registration method for robots to achieve improved accuracy. Registration is a major source of error in robotic surgery, particularly in orthopaedics. The paper describes the design and clinical implementation of a novel method, coined the bounded registration method, applied to minimally invasive registration of the femur. Results of simulations which compare the performance of bounded registration with a standard implementation of the iterative closest point algorithm are also presented, alongside a description of their application in the Acrobot hands-on robot, used clinically for uni-condylar knee arthroplasty.

A novel analytic approach is proposed for determining the singularities of some four degree of freedom (DOF) parallel manipulators (PMs). First, the constraint and displacement of a general 4-DOF PM are analyzed. Second, a common 3 × 4 translational Jacobian matrix Jν and a common 3 × 4 rotational Jacobian matrix Jω are derived, and a 4 × 4 general Jacobian matrix J of the 4-DOF PMs is derived from Jν and Jω. Since a complicated process to determine singularities from the 4 × 6 Jacobian matrix is transformed into a simple process to determine singularity from J, the singularities of the some 4-DOF PMs with 3 translations and 1 rotation, or with 3 rotations and 1 translation, or with combined translation–rotations are analyzed and determined easily by this 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.

This paper proposed a novel three degree of freedom (DOF) parallel manipulator—two translations and one rotation. The mobility study and inverse kinematic analysis are conducted, and a CAD model is presented showing the design features. The optimization techniques based on artificial intelligence approaches are investigated to improve the system stiffness of the proposed 3-DOF parallel manipulator. Genetic algorithms and artificial neural networks are implemented as the intelligent optimization methods for the stiffness synthesis. The mean value and the standard deviation of the global stiffness distribution are proposed as the design indices. Both the single objective and multi-objective optimization issues are addressed. The effectiveness of this methodology is validated with Matlab.

Inverse kinematics (IK) is a nonlinear problem that may have multiple solutions. A modified genetic algorithm (GA) for solving the IK of a serial robotic manipulator is presented. The algorithm is capable of finding multiple solutions of the IK through niching methods. Despite the fact that the number and position of solutions in the search space depends on the position and orientation of the end-effector as well as the kinematic configuration (KC) of the robot, the number of GA parameters that must be set by a user are limited to a minimum through the use of an adaptive niching method. The only requirement of the algorithm is the forward kinematics (FK) equations which can be easily obtained from the Denavit–Hartenberg link parameters and joint variables of the robot. For identifying and processing the outputs of the proposed GA, a modified filtering and clustering phase is also added to the algorithm. For the postprocessing stage, a numerical IK solver is used to achieve convergence to the desired accuracy. The algorithm is validated on three KCs of a modular and reconfigurable robot (MRR).

This paper shows that a well-known causal PD controller plus feedforward solves the global output feedback tracking control problem of robot manipulators, by requiring only the existence of the robot natural damping, no matter how small. To this end, we first demonstrate that a robot controlled by a causal PD is globally input-to-state stable (ISS) with respect to a bounded input disturbance. Then, we prove that the addition of a feedforward compensation renders the error system uniformly globally asymptotically stable. Furthermore, we present a possible extension to more general nonlinear systems and also to uncertain systems.

The paper presents a self-contained approach for the dynamics identification of six degrees of freedom (DOF) parallel robots. Major feature is the consequent consideration of structural properties of such machines to provide an experimentally adequate identification method. The known periodic excitation is modified and enhanced to take the actuator coupling as well as the numerical solution of the direct kinematics into account. The benefits of explicit frequency-domain data filtering are demonstrated. Additionally, a new implementation of the maximum-likelihood estimator allows for automatic tuning of the data filter. The issue of optimal input experiment design is also discussed and substantiated with extensive experiments.

This paper describes a landmark detection and localization using an integrated laser-camera sensor. Laser range finder can be used to detect landmarks that are direction invariant in the laser data such as protruding edges in walls, edges of tables, and chairs. When such features are unavailable, the dependant processes will fail to function. However, in many instances, larger number of landmarks can be detected using computer vision. In the proposed method, camera is used to detect landmarks while the location of the landmark is measured by the laser range finder using laser-camera calibration information. Thus, the proposed method exploits the beneficial aspects of each sensor to overcome the disadvantages of the other sensor. While highlighting the drawbacks and limitations of single sensor based methods, an experimental results and important statistics are provided for the verification of the affectiveness sensor fusion method using Extended Kalman Filter (EKF) based simultaneous localization and mapping (SLAM) as an example application.

Artificial intelligence techniques applied to control processes are particularly useful when the elements to be controlled are complex and can not be described by a linear model. A trade-off between performance and complexity is the main factor in the design of this kind of system. The use of fuzzy logic is specially indicated when trying to emulate such human control actions as driving a car. This paper presents a fuzzy system that cooperatively controls the throttle and brake pedals for automatic speed control up to 50km/h. It is thus appropriate for populated areas where driving involves constant speed changes, but within a range of low speeds because of traffic jams, road signs, traffic lights, etc. The system gets the current and desired speeds for the car and generates outputs to control the two pedals. It has been implemented in a real car, and tested in real road conditions, showing good speed control with smooth actions resulting in accelerations that are comfortable for the car's occupants.

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.

In the present paper, the kinematics of a three-degree-of-freedom spherical wrist is investigated. The wrist consists of a fixed base connected to a moving platform by three identical legs, each with a RRUR chain (R and U denote a revolute pair and a universal pair, respectively). For each leg, the first R pair is to be considered actuated. Although in previous works the kinematics synthesis of this architecture was carried out, no detailed studies were presented on the kinematic issues of the wrist. This paper presents the mobility analysis, the direct and inverse position kinematics, the differential kinematics of the manipulator including inspection on the jacobian matrix and the analysis of the singularities. The geometrical condition matched in case of mechanical interference between legs is addressed, too. A numerical example of the manipulator kinematics was performed to obtain the workspace, the condition number and the mechanical inteference condition.