Force and position sensors have been widely used in robots to realize compliance and precise control. Traditional force/position control methods were studied and developed by the inverse dynamics for decades. Generally speaking, the controller contains two parts: One is the error-driven part that guarantees system stability; another is the identification model of inverse dynamics that can compensate for system influence. In practical control engineering, a system inverse dynamics or its identification model is not easy to obtain, even when using nonlinear estimation methods. Moreover, the complicated control algorithm cannot be implemented in on-board microprocessors because of the limited speed and memory. Thus, a simplified control method using a forward system model is introduced in this paper. Since the direct dynamics of the system can be more easily obtained than the inverse dynamics, this, in turn, simplifies the control structure and increases control speed. Therefore, the proposed control policy has a wider practical application.

This paper provides a solution to the composite adaptive output feedback tracking control problem for robotic manipulators. The proposed controller utilizes an update law that is a composite of a gradient update law driven by the link position tracking error and a least squares update law driven by the prediction error. In order to remove the controller's dependence on link velocity measurements, a linear filter and a new prediction error formulation are designed. The controller provides semi-global asymptotic link position tracking performance. Experimental results illustrate that the proposed controller provides improved link position tracking error transient performance and faster parameter estimate convergence in comparsion to the same controller using a gradient update law.

In this paper we present an experimental comparison between different decentralized controllers for industrial robot manipulators. In spite of the fact that robot manipulators are highly nonlinear and coupled multivariable systems, decentralized controllers have been widely adopted in industrial environments for trajectory tracking, because of their simplicity and their fault tolerance feature. Different kinds of controllers have been investigated: the typical PID-based controller, a nonlinear three-term controller devised by Tarokh, and a variable structure control law, a discontinuous integral control, both in the continuous and in the discretised version. Allowances are made for the tuning of the parameters in order to obtain low tracking errors. Results show that better performances are obtained by controllers other than PID, especially by the discontinuous integral control, so that they appear to be particularly appropriate for the use in industrial robots.

The goal of this paper is to present a new method to control pushing operations with several fingers. We take into account some dynamical aspects that have not yet been investigated in pushing studies such as the object's center of mass acceleration correction and optimal force distribution. To do this, we use a general method for multi-chain mechanisms based on a dynamical control with finger coordination. We first detail the problems encountered in this type of manipulation and the way to take these points into account with specific constraints definition for the support contact. According to the parameters of the model such as optimization criterion and object characteristics, we present simulation results of object pushing with two fingers for a rotational and translational motion.

The peg-in-hole insertion process is the most common task in the robotic/automatic assembly industry. However, the inaccuracy of the assembly robot in positioning the inserted peg into the hole due to the uncertainty of the assembly environment, represents an obstacle in this area of automation. To overcome this problem, complex and expensive equipment has been designed. The objective of this paper is to provide an in-depth understanding of the chamferless peg-hole assembly, by showing the geometrical, dynamical conditions for a successful assembly operation. Also, the results of this analysis have been simulated to demonstrate the chamferless peg-hole insertion process.

Virtual sensors (software abstractions to support programming of sensor use) have been shown to have software-engineering benefits. A sensor integration system is required to support them. We examine the general requirements of such systems and consider the important design requirements. An idealised architecture, ViSIAr, is proposed to serve as a framework for designing and constructing them. Illustrative examples are provided.

A method of data segmentation, based upon robust least K-th order statistical model fitting (LKS), is proposed and applied to image motion and range data segmentation. The estimation method differs from other approaches using versions of LKS in a number of important ways. Firstly, the value of K is not determined by a complex optimization routine. Secondly, having chosen a fit, the estimation of scale of the noise is not based upon the K-th order statistic of the residuals. Other aspects of the full segmentation scheme include the use of segment contiguity to: (a) reduce the number of random sample fits used in the LKS stage, and (b) to “fill-in” holes caused by isolated miss-classified data.

During the last two decades a large amount of effort and attention has been paid to the problem of designing and controlling dextrous robotics hands. The possible application background ranges from telerobotics to upper limb prosthetics, while actual industrial developments are mainly limited to specific grippers and tools. Classical problems related to dextrous hand design are kinematics of multifingered hands, development of proper actuation technologies and redundant tendinous systems for transmission. As far as hand control is concerned, grasp preshaping, planning and synthesis are of major concern, while sensor guided hand operation is still a matter of research. The present work reviews the above mentioned hand design and control issues trying to throw some light on the Babel-like confusion encountered when looking at present literature on dextrous hand design and specially control. Most actuation and transmission technologies, as well as control approaches, are studied and classified.

In this work a new concept of designing two degree of freedom (2-DOF) planar parallel manipulators (PPMs) is presented. With this design the manipulator's workspace can be increased by increasing the number of cells in the manipulator. A general dynamic model is formulated for the manipulator with any number of cells. The model is adapted for SCARA and ADEPT configurations, and a new approach for balancing these type of manipulators is proposed.

Optimal control of fingertip force during grasping operation by multifingered robotic end effectors is an important consideration. Determination of optimal fingertip force is, however, very complicated due to the involvement of a number of contact parameters at the finger-object interface including the mass of the object and the frictional properties of the contact surfaces. Modelling of various contact parameters is computationally overloading, which may not be tenable in practical situations where objects of different mass and material are available. Also for an unknown and unstructured environment, these properties may not be known in advance. This paper presents a controller based on fuzzy logic which is capable of performing optimal grasp of objects without knowing their mass and frictional properties. The controller also accounts for stability and dynamic aspects of the grasp. The experimental results of the implementation are presented.