In this paper we present the results obtained from the implementation of a robust position/force controller on a two-degree-of-freedom direct drive robot. The controller is based on the theoretical work presented in references 1 & 2, which guarantees Globally Uniformly Ultimately Bounded (GUUB) position tracking error and bounded force tracking error. The controller accomplishes this stability result in spite of robot model uncertainty and only requires; joint position and velocity measurements, end-effector force measurements, and bounds on the model parameters. Experimental results described in this paper serve to verify the theoretical claims.

The use of ultrasonic range transducers is an inexpensive method of obtaining information about the environment surrounding a robotic System. However, ultrasonic ranging suffers from various shortcomings, one of the major being the production of unreliable data caused by specular reflection.

This work presents an original approach to overcoming the problem of unreliable ultrasonic range data which is caused by specular reflection of the ultrasonic beam. The approach is shown to discriminate between reliable and unreliable data, thus enhancing the role of the ultrasonic range transducer in robotic applications.

In this paper, an approach to modelling of a robotic assembly cell is proposed and a method for managing the cell operation is described using a knowledge base. Since the modelling structure is based on the concept of the state variable, the relationships between states are described by the state transition map (STM). The knowledge-bases for state transition and assembly job information are obtained from the STM and the assembly job tree (AJT), respectively. Using the knowledge-base, the System structure is discussed in relation to both managing the cell operation and evaluating the performances. Finally, a simulation algorithm is presented with the simulation results to show the significance of the proposed modelling approach.

This paper aims at contributing to a sub-symbolic, feedback-based “theory of robotic grasping” where no full geometrical knowledge of the shape is assumed. We describe experimental results on grasping 2D generic shapes without traditional geometrical processing. Grasping algorithms are used in conjunction with a vision system and a robot manipulator with a three-fingered gripper is used to grasp several different shapes. The altorithms are run on the shape as it appears on the computer screen (i.e. directly from a vision system). Simulated gripper ringer with virtual sensors are configured and positioned on the screen whose inputs are controlled by moving their position relative to the image until an equilibrium is reached among the control systems involved.

Today's industrial machines and manipulators have no capability to learn by experience. Performance and productivity could be greatly enhanced if a machine could modify its operation based on previous actions. This paper presents a learning control scheme that provides the ability for machines to utilize their past experiences. The objective is to have machines mimic the human learning process as closely as possible. A data base is formulated to provide the machine with experience. An optical infrared distance sensor is developed to inform the machine about objects in its working space. A learning control scheme is presented that utilizes the sensory information to enhance machine performance in the next trial. An adaptive scheme is proposed for the modification of learning gain matrices, and is implemented on an industrial robot. Experimental results verify the potentials of the proposed adaptive learning scheme, and illustrate how it can be used for improvement of different manufacturing processes.

We present an analysis of currently available user language facilities for sensor-based programming of robot assembly tasks. A common criterion is defined that a language support for sensor-based programming must satisfy. Finally, drawing upon a novel mechanism of generalized exception, we present a framework for a complete solution of these problems in a high level block structured and complex language, as well as a possible implementation of such tools.

An analysis is presented in this paper for the equilibrium of a class of parallel manipulators resembling the Stewart platform in a general form. General coordinates and 4 x 4 homogeneous transformations are employed to arrive at exact expressions for the force distribution in all six legs given the general 6-dimensional wrench (generalized force) at the upper platform of a parallel manipulator. Numerical examples are carried out to examine the validity of the approach and the accuracy of the numerical technique employed.

Structural and control flexibilities affect the absolute precision of serial manipulators. A semi-flexible kinematic model is developed, to improve the absolute static precision. It expands the solid body model by incorporating a spring effect for each joint and a beam effect for each link. Simulation results confirm the adequacy of the model. The dependencies existing between the articulate posture of the manipulator, the effects of the external efforts and the gravitational load on the global structure are properly described. The identifiability of the added parameters is explored on a RR planar robot. It requires efforts and pose errors to be known in the tool frame only.

In the tracking control of manipulators via the sliding scheme, it may happen that sometimes, because of various inaccuracies, the definition of the actual sliding surface involves errors terms which may be either deterministic or, on the contrary, stochastic. This paper considers this last case and shows how one can estimate the new performances of the system so disturbed. A stochastic Hamilton's principle is applied, by combining the Lagrange parameter technique with results of the dynamic programming approach.