A new control strategy based on the singular perturbation method and integral manifold concept is introduced for flexible-joint manipulators with joint friction. In controllers so far developed based on the singular perturbation theory, the dynamics of actuators of flexible-joint manipulators are partially modelled, and the coupling between actuators and links is ignored. This assumption leads to inaccuracy in control performance and error in trajectory tracking which is crucial in high-precision manipulation tasks. In this paper, a comprehensive dynamic model which takes into account the coupling between actuators and links is developed and a composite controller is then designed based on the singular perturbation theorem and integral manifold concept. To overcome the joint friction, a novel method is introduced in which a linear feed-forward torque is designed using the principle of work and energy. Finally, the experimental set-up of a single rigid-link flexible-joint manipulator in the Robotics Laboratory at the University of Saskatchewan is used to verify the proposed controller. Experimental results employing the new controller show that the trajectory tracking error during and at the end of the motion of the robot manipulator is significantly reduced.

In this paper a new approach based on the generalized momentum is used to obtain the dynamic model of a six degrees-of-freedom (dof) parallel manipulator. First, the system dynamic equations are obtained supposing the manipulator base platform is fixed. Afterwards, the dynamic model is extended to the case of a moving base platform. This could be important in a macro/micro robotic application, where a small manipulator is attached in series to a big manipulator. Simulation results of a macro/micro robotic system are presented and the contribution of the base platform motion to the total actuating forces is shown.

This paper discusses analytical and deterministic models for a plane curve with minimum deformation that may be utilized in planning the motion of elastic linear objects and investigating the inverse kinematics of a hyper-redundant robot. It usually requires intensive computation to determine the configuration of elastic linear objects. In addition, conventional optimization-based numerical techniques that identify the shape of elastic linear objects in equilibrium involve non-deterministic aspects. Several analytical models that produce the configuration of elastic linear objects in an efficient and deterministic manner are presented in this paper. To develop the analytical expressions for elastic linear objects, we consider a cantilever beam where the deflections are determined according to the Euler–Bernoulli beam theory. The deflections of the cantilever beam are determined for prescribed constraints imposed on the deflections at the free end to replicate various elastic linear objects. Deflections of a cantilever beam with roller supports are explored to replicate elastic linear objects in contact with rigid objects. We verify the analytical models by comparing them with exact beam deflections. The analytical model is precisely accurate for beams with small deflections as it is developed on the basis of the Euler–Bernoulli beam theory. Although it is applied to beams undergoing large deflections, it is still reasonably accurate and at least as precise as the conventional pseudo-rigid-body model. The computational demand involved in using the analytical models is negligible. Therefore, efficient motion planning for elastic linear objects can be realized when the proposed analytical models are combined with conventional motion planning algorithms. We also demonstrate that the analytical model solves the inverse kinematics problem in an efficient and robust manner through numerical simulations.

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.

In the past years a large number of new surgical devices have been developed to improve the operation outcomes and reduce the patient's trauma. Nevertheless, the dexterity and accuracy required in positioning the surgical tools are often unreachable if the surgeons are not assisted by a suitable system. Since a medical robot works in an operating room, close to the patient and the medical staff, it has to satisfy much stricter requirements with respect to an industrial one. From a kinematic point of view, the robot must reach any target position in the patient's body, being as less invasive as possible for the surgeon's workspace. In order to meet such requirements, the right robot structure has to be chosen by means of the definition of suitable kinematic performance indices.

In this paper some task-based indices based on the robot workspace and stiffness are presented and discussed. The indices will be used in a multiobjective optimization problem to evaluate best robot kinematic structure for a given neurosurgical task.

In this paper, a control design methodology for a new class of modular robots, so-called “uni-drive modular robots” is introduced. Uni-drive modular robots have a substantial advantage over regular modular robots in terms of the mass of each module since then employ only a single drive for powering all the joints. The drive is mounted at the robot base and all joints tap power from this single drive using clutches. By controlling the engagement time of the clutches, the position and velocity of the joints are regulated. After reviewing the structure of the uni-drive modular robot, a self-expansion formula to generate the dynamics of the robot is introduced. The control of uni-drive n-module robots is realized by blending independent joint control and theory of variable structure systems via a pulse width modulation technique. A uni-drive modular robot is used to conduct simulations and validate the control design technique.

This paper deals with a comparative study of two planar two degrees of freedom parallel mechanisms: one with 2-RRR and the other with 3-RRR structures. For a fair comparison, both 3-RRR and 2-RRR mechanisms are symmetrical. The kinematics and Jacobian matrix of the two mechanisms are studied. Conditioning index, stiffness index and payload index are proposed to compare the condition, stiffness and payload performance of the two mechanisms. The results show that the 2-RRR and 3-RRR mechanisms have the similar condition performance, and the planar 3-RRR mechanism has better payload and stiffness performance than the 2-RRR one.

Surgical robotics is a growing discipline, continuously expanding with an influx of new ideas and research. However, it is important that the development of new devices take account of past mistakes and successes. A structured approach is necessary, as with proliferation of such research, there is a danger that these lessons will be obscured, resulting in the repetition of mistakes and wasted effort and energy. There are several research paths for surgical robotics, each with different risks and opportunities and different methodologies to reach a profitable outcome. The main emphasis of this paper is on a methodology for ‘applied research’ in surgical robotics. The methodology sets out a hierarchy of criteria consisting of three tiers, with the most important being the bottom tier and the least being the top tier. It is argued that a robotic system must adhere to these criteria in order to achieve acceptability. Recent commercial systems are reviewed against these criteria, and are found to conform up to at least the bottom and intermediate tiers, the most important first two tiers, and thus gain some acceptability. However, the lack of conformity to the criteria in the top tier, and the inability to conclusively prove increased clinical benefit, is shown to be hampering their potential in gaining wide establishment.

Figures 2 and 5 were incorrectly reproduced in the above publication (Ratajczak et al. 2009). The figures are reproduced below in their correct form. Fig. 2.

Task-priority algorithm (both S1 and S2).

Single-task algorithm (only S1).

To realize the automation of biomaterial cutting, the interaction between the blade and biomaterial deserves insight understanding. In this paper, a blade-compression cutting model is developed. The influences from the material properties, deformation, and blade properties on the cutting force are thoroughly explained. An approach to describe the sharpness of a blade is provided and its applicability is experimentally demonstrated. Based on the material property and knife sharpness property, the required force to realize compression cut can be predicted. This provides the reference force trajectory for the automation of biomaterial compression cutting.