In this paper a pneumatic vibratory wrist operated with a PWM controller is developed for robotic assembly. In the vibratory assembly system, the vibratory wrist can perform random search motion of a hole to compensate the position error at the early stage of an insertion process. Since the vibration characteristics of the wrist, such as the amplitude and trajectory of the vibration, are critical to assembly performance, they are experimentally investigated for various system controller parameters. In addition, a series of insertion experiments are performed to evaluate the assembly performance of the proposed wrist. The results show that within a wide range of operating conditions the wrist vibration can effectively compensate for large positioning errors when this wrist is used for a chamferless peg-in-hole task.

This paper reports on a continuation of research activities at the Loughborough University of Technology (LUT) which are aimed at evolving second generation pneumatic drives and provides an introduction to various aspects which must be considered in the design and use of industrial pneumatic servo-driven robots. The paper illustrates how a new generation of fast and accurate pneumatic servo drives, demonstrating excellent performance/cost characteristics, will become available and will rival electric and hydraulic counterparts in many areas of industrial control.

The need for fault tolerant mechanisms in flexible manufacturing systems is described and previous work on diagnosis in robotics and other areas is considered. Fundamental difficulties in the analysis of robot cell malfunctions are described and a glossary of terms useful in this area is presented. Limited observational data on the occurrence of faults in assemblies are reported. Finally a proposal for an experimental mechanism for diagnosis within a knowledge rich supervisory system is explored.

Intelligent control of mobile systems allows for hierarchical structures that utilize sensory data with various levels of accuracy. This paper discusses a rule-based approach for the control problem. The assumed inexactness in world description is represented by fuzzy memberships, and the state space is discretized into a linguistic vocabulary. Fuzzy motion control rules that have been experimentally derived, are then used in a fuzzy inference mechanism to give the final control command to robot actuators. Finally, the developed algorithm is tested for real-time control applications.

A method for planning minimum time joint trajectories for robot manipulators is discussed. The minimum time trajectory planning problem for manipulators is one of the minimum time control problems of non-linear systems. The optimal input torque/force is of a bang-bang type, except for the singular control derived from the Maximum Principle. An algorithm for generating a bang-bang control is proposed. In the algorithm, the switching time vector is updated to decrease the final state error. The proposed algorithm is applied to a simple manipulator with two links, and the solution by this algorithm is compared with the sub-optimal solution obtained by another approximate method.

The Autonomous Robot Architecture (AuRA) provides multi-level representation and planning capabilities. This paper addresses the task of navigational path-planning, which provides the robot with a path guaranteed to be free of collisions with any modeled obstacles. Knowledge supporting visual perception can also be embedded, facilitating the actual path traversal by the vehicle.

A multi-level representation and architecture to support multi-sensor navigation (predominantly visual) are described. A hybrid vertex-graph free-space representation based upon the decomposition of free space into convex regions capable for use in both indoor and limited outdoor navigation is discussed. This “meadow map” is produced via the recursive decomposition of the initial bounding area of traversability and its associated modeled obstacles. Of particular interest is the ability to handle diverse terrain types (sidewalks, grass, gravel, etc.) “Transition zones” ease the passage of the robot from one terrain type to another.

The navigational planner that utilizes the data available in the above representational scheme is described. An A* search algorithm incorporates appropriate cost functions for multi-terrain navigation. Consideration is given to just what constitutes an “optimal” path in this context.

An off-line programming station for a robotised welding cell is presented. In this context the choice of a kinematic inversion method applied to the simulation of robots is discussed.

A direct inversion method is developed in the case of 5-axes robots of plane geometry and for a task presenting a symmetry of revolution. It uses the geometry of the tool and of the robot and vectorial calculations very well adapted to this particular case. The results presented validate the choice of this method for a specialised programming environment.

The development of robot languages has followed a pattern similar to that of conventional programming languages, where robot languages have been based on an existing programming language. This paper first identifies the use of an existing base as one way of developing robot programming languages, and discusses the areas of difficulty in this approach. Then, on-line and off-line programming of robots is discussed and the requirements of robot programming languages that are different to those of non-specialised programming languages are presented. A discussion and evaluation of some programming languages in terms of their appropriateness for use as the base for an intelligent robot programming language is presented. This leads to the conclusion that no current language forms an adequate base for intelligent robot programming languages. What is needed as a base is a language for use in the artificial intelligence domain, that incorporates real-time facilities.