A global optimal control algorithm was developed with the aim of finding a control which satisfies some special requirements in the sense of obtaining singular position free movement of the redundant robot mechanism. The solution of the developed global optimal control algorithm is a boundary value problem. The additional constraints in the boundary value problem were constructed with the use of an optimization process. The usefulness of the developed global optimal control algorithm is demonstrated by the example of the 3 DOFs planar redundant robot mechanism of SCARA type.

This paper describes an efficient and fast algorithm for finding the minimum distance between two convex polyhedrons in a three dimensional space. To obtain the minimal distance, the proposed computational scheme is based on a direct approach to minimizing the distance function which produces a succession of optimal search directions along object boundaries. This algorithm combines the gradient projection method'; and an additional optimal search direction when the gradient projection method leads to a zigzagging phenomenon. In this case, the additional optimal search direction accelerates significantly the convergence of the process. Extensive numerical experiments with convex polyhedra show the performance of this algorithm when compared with that of previous approaches. The proposed algorithm may be very helpful in solving the computation of minimal distance between a pair of convex sets, the collision detection problem or to track the closest points of moving convex objects.

This special issue in Robotica contains papers from Japanese authors on microrobots and distributed microactuators. Advances in technology made possible progress in the realm of small but complicated microsystems that include different elements, such as sensors, circuits and actuators. Microsystems are also called micromachines or microelectromechanical systems (MEMS); microsystems which move like insects are termed microrobots.

In the field of robotic applications based on the coordinated motion of two manipulators, it seems that very few control schemes work efficiently. The best way to achieve the simultaneous control of object trajectory and forces applied to it, is to implement control schemes that are extended versions of one arm hybrid force'position control. The aim of this paper is not to review all existing solutions but rather to analyze and compare them from simulation results with a new solution presented here. The control scheme is an application of the one arm hybrid external control that we had previously developed. The main results of this theory are summarized in this paper. This radically new approach for a cooperation task has some advantages compared to other methods mentioned in this paper.

In this paper, an adaptive learning (A-L) control scheme is proposed for cooperation of two manipulators handling a rigid object with model uncertainties. For robots performing repetitive cooperating tasks, their operations are decomposed into two modes: the single operational mode and the repetitive operational mode on which the A-L controller is based. In the single operational mode, the controller is a learning based adaptive controller in which the robotic parameters are updated by using the information of the previous operation. In the repetitive operational mode, the controller is a model-based iterative learning controller. The advantages of the A-L controller lie in the fact that it can improve the transient performance as robots repeat operations at a high speed of the learning convergence. Simulation results ascertain that the A-L algorithm is effective in controlling two cooperated robots with model uncertainties.

This paper discusses suitable mechanisms and functions of a mobile microrobot from the point of view ofscale effects. Several assumptions are made using animalscaling. A large scale model is shown to demonstrate these mechanisms. Moreover, microsized models have been built on silicon wafers by using polysilicon as rigidplates and polyimide as elastic joints. The results showthat suitable mechanisms and functions may be different from those of a conventional robot.

The basic robot control technique is the model based computer-torque control which is known to suffer performance degradation due to model uncertainties. Adding a neural network (NN) controller in the control system is one effective way to compensate for the ill effects of these uncertainties. In this paper a systematic study of NN controller for a robot manipulator under a unified computed-torque control framework is presented. Both feedforward and feedback NN control schemes are studied and compared using a common back-propagation training algorithm. Effects on system performance for different choices of NN input types, hidden neurons, weight update rates, and initial weight values are also investigated. Extensive simulation studies for trajectory tracking are carried out and compared with other established robot control schemes.

Many studies on control of dynamic biped walking have been done in the past two decades. While the biped dynamics is highly nonlinear, the stability analysis, if done, is usually based on a linearized model. The validity of the linearized model may become questionable if the walking involves states that are too far away from the operating point. In this paper, an approach for evaluating the robustness based on the linearized Poincare map is suggested and examined. The Poincare map is a useful tool to investigate the periodic motion of a dynamic system. Using the Poincare“ map, one can study an associated discrete time map instead of studying the continuous time system directly. Investigation of stability of a periodic motion can be reduced to the study of the stability of a fixed point of the Poincaré map. The computational method that results in a measurement for evaluating the robustness of biped locomotion is developed. Our simulation study has verified that the suggested measurement is a good indicator.

This paper proposes a new algorithm, known as the Segmentation Algorithm, which provides model-based, real-time, whole-arm collision avoidance for telerobotic applications. The work presented here is an extension and modification of potential field theory. Novel aspects of the algorithm include the application of a hierarchical segmentation technique to minimize on-line processing and the development of procedures which account for workspace object translation, rotation, and grasping. The'SA outputs torques, which, when applied to the control arm, prevent the teleoperator from driving the remote arm into a collision. The teleoperator actually feels workspace objects that are spatially close to the remote arm—an experience known as virtual force-reflection. The SA's performance has been analyzed in terms of its speed and efficiency vis a vis various system parameters, including workspace object distribution, size, and number. Simulation results show that the SA succeeds in providing real-time collision avoidance where less elegant brute force algorithms fail.

In this paper, a very inexpensive, lightweight and simple wrist mechanism is introduced. This wrist displays nonlinear torsional vibrations. This differs from conventional wrists in that structural flexibility in the mechanism is allowed to occur by design. In this paper, the dynamic equations of this wrist are derived. System identification techniques are then employed to obtain a linearized model. Various control strategies are studied. It is shown that the input-output feedback linearization technique is not feasible for these nonlinear dynamic equations. It is also shown that the use of conventional rigid body PID controllers on this proto-type is inadequate. A tracking controller which compensates for the flexible dynamics of the wrist is implemented with encouraging results. This controller allows the end-effector to be placed at an arbitrary orientation with little vibration. The effect of the controller is to make the wrist appear to have a much higher structural stiffness. The compliant nature of this wrist allows simple force control strategies to be implemented. It is the combination of the wrist with the control algorithm which makes this design viable.

This paper presents a practical approach for the point-to-point control of elastic-jointed robot manipulators. With the proposed approach only position and velocity feedback are referenced, as opposed to most of the existing control schemes of elastic-jointed manipulators which require additional acceleration and/or jerk feedback. To guarantee the robustness of the controller, it is designed on extreme parameter uncertainties due to highly elastic joints of manipulators and energy motivated Lyapunov functions are used to derive the control law. Four pertinent controller gains are chosen in light of the on-line position and velocity feedback of the links and joint sensors. Through a simulated experimental verification, it is demonstrated that the designed simple position and velocity feedback controller, similar to that used for rigid-jointed robots, can globally stabilize the elastic-jointed robot for a bounded reference position. In addition, the tracking performance of the controller reveals that this simple control algorithm is robust in terms of joint flexibility. And the simplicity of the presented control algorithm, as compared to other model-based techniques for flexiblejoint robots, is particularly advantageous. Even though the simulated experiments are conducted on a single-link flexible joint robot, control law derived in this paper has general meaning for multi-link flexible joint robots.

Recent topics in the development of micromagneticactuators in Japan are reviewed. Electromagneticmicroactuators less than 1 mm in diameter, e.g.micromotor, and microvalves have been fabricated andtheir high performance has been demonstrated. A newtype microactuator based upon magnetostriction has alsobeen developed and has shown a large cantileverdeflection. In addition, some models of the microrobotsusing micromagnetic actuators were able to move using awireless remote power supply.

In this paper sliding mode motion design is considered for nonlinear plants which are linear with respect to control input. The dynamics of the robotic manipulators is treated with and without those of the actuators. When the dynamics of the actuators is included a design of the sliding modes for the systems with discontinuous control is performed. If actuators' dynamics is negelected the control is assumed to be continuous quantity. By combining the variable structure systems and Lyapunov designs a new algorithm is developed which has all the good properties of the sliding mode systems while avoiding unnecessary discontinuity of the control thus eliminating chattering. Neither the explicit calculation of the equivalent control, nor high gain inside the boundary layer are used. The parameters of the control depend on the plant's gain matrix, and the gradients of the sliding mode manifold. This control method is then applied to develop a unified control strategy for the motion control systems including the path tracking control, the impedance control and the force control of a robotic manipulator. It is shown that all these tasks can be formulated in the same mathematical form in which selected so-called sliding mode functions must track their references. In this way the systems state is forced to remain on the selected manifold in the state space after reaching it. The solution is interpreted in both the Joint space and the Work space for n -degrees of freedom robotic manipulators.

Current industrial robots are highly non-linear systems. However, the control strategies in most commercially available robots largely ignore the non-linearity. The resulting linear approximations are only valid at low speeds. Any improvement would allow robots to move faster and hence be more productive. There has been much academic research into robot control, but this has almost always separated the control and the trajectory planning. In this work we seek to combine these tasks and hence simplify the computations required. We investigate how to control a general robot in such a way that it's gripper follows straight line, circular or helical paths. These simple paths are both one parameter subgroups for the group of proper rigid motions and geodesies for certain metrics on the group. This suggests a non-linear feedback control law which turns the closed loop dynamics of the robot into the equations for geodesies. Although these equations are not completely stable we are able to modify the control law so that the resulting closed loop dynamics are stable. Hence, the end-effector of the robot will follow straight line, helical or circular trajectories.

A new mathematical formulation of robot and obstacles is presented such that for on-line collision recognition only robot joint positions in workspace are required. This reduces calculation time essentially because joint positions in workspace can be computed every time from the joint variable through robot geometry. It is supposed that the obstacles in the workspace of the manipulator are represented by convex polygons. For every link of the redundant robot and every obstacle a boundary ellipse in 2D is defined in workspace such that there is no collision if the robot joints are outside these ellipses. First, some methods are presented for the automatic determination of these ellipse functions from the obstacle and robot data. Then, the boundary ellipse functions are used as optimization criterion in a collision-avoidance method. The method permits the tip of the hand to follow a given path in the free space while the kinematic control algorithm maximizes the boundary ellipse function of the critical link. The effectiveness of the proposed methods is discussed by theoretical considerations and illustrated by simulations of the motion of three- and four-link manipulators between obstacles.

The main objective of this work is to study the performance of a flexible single hub-arm system. The equations of motion are derived using the extended Hamilton principle. The Liapunov functional is used as a condition for the stability analysis. The Liapunov functional is considered as the sum of the internal energy of the flexible beam. The required drive torque was obtained directly through the solution of the inverse dynamic problem. Although the flexible link is nonminimum phase in nature, the use of Liapunov and the PD controller guarantee the causality for the stable case. The effects of tip mass as well as its inertia in the case of stable and asymptotic stable systems were investigated to ensure the validity of this procedure.

A technique for open-loop minimum time planning of time-histories of control torques for robotic manipulators subject to constraints on the control torques using evolutionary algorithm is presented here. Planning is carried out in joint space of the manipulator and the path is represented as a string of via-points connected by cubic spline polynomial functions. Repeated path modification is done by using the evolutionary algorithm to search for a time-optimal path. Time taken to traverse over a particular path is calculated by reducing the dynamic equations of motion over that path in terms of a path parameter and then calculating the time optimal-control over that path.