ROBOTICS AND AUTOMATION WORLDWIDE

1. Australia

Robot Etherbot. At Monash University researchers report the development of a portable mobile robot system called ‘Etherbot’. It carries no computer aboard but instead, the calculations required to determine the robot's location and the shortest obstacle-free path to a desired destination are carried on a nearby workstation. This is a Silicon Graphics workstation with which the robot communicates via a 2Mb radio Ethernet link. This reduces the payload and increases the time that the robot can travel before its batteries need recharging.

A basic problem in the development of an intelligent vehicle/highway system (IVHS), or an autonomous mobile robot system (AMRS) is to find suitable input controls which can be used to drive the vehicle between any two configurations. In this paper a trajectory generation problem for a four-wheel-steering tractor/semi-trailer system is investigated, and it is shown that this nonholonomic constraint problem can be converted into one of finding fitting-functions satisfying certain necessary boundary conditions. Proposals for control laws are presented and simulation results for a lane change manoeuvre are given.

One of the most difficult challenges in mobile robotics is real-world navigation. A real world can change suddenly and this change makes the robot relinquish planning actions in advance. In order to overcome such a change, behavior-based navigation was introduced. However, it had a difficulty in planning deliberate actions and in communicating with humans.

We propose a new control strategy combining both the merits of behavior-based and planner-based approaches. The architecture consists of three major parts: Behaviors, Planner, and Coordinator. The Planner plays two important roles: 1) as a flexible human interface and 2) as the planner itself. The Coordinator serves as an interface between Behaviors and Planner and guides Behaviors to accomplish meaningful tasks according to the guidelines from the Planner and the Position estimator.

We also provide a brief description of the intelligent mobile robot CAIR-2 and for '95 IJCAI/AAAI Robot Competition and Exhibition when the robot was placed first in the Office Delivery event.

This paper presents a hybrid approach to optimize the counterweight balancing of a robot arm. A new technique that combines an artificial intelligence technique called the genetic algorithm (GA) and the weighted min-max multiobjective optimization method is proposed. These techniques are included in a system developed by the authors, called MOSES, which is intended to be used as a tool for engineering design optimization. The results presented here show how the new proposed technique can get better trade-off solutions and a more accurate Pareto front for this highly non-convex problem using an ad-hoc floating point representation and traditional genetic operators. Finally, a methodology to compute the ideal vector using a genetic algorithm is presented. It is shown how with a very simple dynamic approach to adjust the parameters of the GA, it is possible to obtain better results than those previously reported in the literature for this problem.

In this paper a path planning method for off-line programming of a joint robot is described. The method can automatically choose the easiest and safest route for an industrial robot from one position to another. The method is based on the use of a Self Organised Feature Map (SOFM) neural network. By using the SOFM neural network the method can adapt to different working environments of the robot. According to test results one can conclude that the SOFM neural network is a useful tool for the path planning problem of a robot.

Our contribution tackles the problem of learning to understand anaphoric references in the context of robotic machine learning; e.g. Get the large screw. Put it in the left hole. Our solution assumes the probabilistic theory of learning spelt out in earlier publications. Associations are formed probabilistically between constituents of the verbal command and constituents of a presupposed internal representation. The theory is extended, as a first step, to anaphora by learning how to distinguish between incorrect surface depth and the correct tree-structure depth of the anaphoric references.

This is an extension of previous work which used an artificial neural network with a back-propagation algorithm and a lookup table to find the inverse kinematics for a manipulator arm moving along pre-defined trajectories. The work now described shows that the performance of this technique can be improved if the back-propagation is made to be adaptive. Also, further improvement is obtained by using the whole workspace to train the neural network rather than just a pre-defined path. For the inverse kinematics of the whole workspace, a comparison has also been done between the adaptive back-propagation algorithm and radial basis function.

This paper presents an investigation into the utilisation of sequential and parallel processing techniques for the real-time simulation of a flexible manipulator system. A finite dimensional simulation of the system is developed using a finite difference approximation to the governing dynamic equation of the manipulator. The developed algorithm is implemented on a number of uni-processor and multi-processor, homogeneous and heterogeneous, parallel architectures. A comparison of the results of these implementations is made and discussed, on the basis of real-time processing requirements in the simulation and control of flexible manipulator systems.

In standard pseudoinverse-based approaches to treat redundant manipulators, the vector of joint increments that corresponds to a desired motion in the space of the secondary task is projected in the Jacobian null space associated with the primary task. In general, this projection may distort the projected vector, so that the secondary task may not adequately be executed. A usual remedy is to rotate the null space projection operator by using a special-purpose weighting matrix. The problem, however, is that this rotation cannot be enforced arbitrarily since it influences the manipulator's performance. In our work we propose an algorithm that is independent on the chosen null space operator and always provides the best attainable motion in the space of the secondary task. Hence, the secondary task is executed more efficiently and the numerical procedure is more robust. A series of numerical experiments confirmed these results.

This paper reports the results of an experimental study, which was conducted to evaluate the performance and implementation aspects of a generalized predictive control (GPC) technique to an electro-hydraulic positioning actuator. Poor dynamics and high nonlinearities form part of the difficulty in the control of hydraulic functions which make the application of adaptive controls an attractive solution. The applicability of GPC to the position control of hydraulic manipulator has been investigated through computer simulations in the literature. However, there is no experimental record of applying this technique to an actual hydraulic system. A suitable plant model is established and recursive U-D factorization technique is adopted for on-line estimation of time-varying plant parameters. Experimental results are obtained from a laboratory electrohydraulic actuator test stand. Various benchmark tests, comprising step and tracking inputs, demonstrate good performance and the promise of the technique. In spite of significant actuator dynamics (control voltage saturation, flow nonlinearity and dry frictional nonlinearity in the hydraulic actuator), successful control tests could be performed repetitively.

SIXTH ANNUAL SYMPOSIUM ON HAPTIC INTERFACES

The Sixth Annual Symposium for Haptic Interfaces for Virtual Environment and Teleoperator Systems was held on Nov. 17–18, 1997 in Dallas, Texas. Haptic interfaces are devices that allow human–machine interaction through force and touch. Areas of application include, but are by no means limited, to telemanipulation (for work in hazardous or challenging environments such as space exploration, undersea operations, microsurgery and minimally-invasive surgery, and hazardous waste clean-up) and virtual environments (for realistic interactions with computer simulations in critical procedure training, architectural design, product prototyping, and data visualization).

WORLD MANUFACTURING CONGRESS '97 18–21 NOVEMBER 1997, MASSEY UNIVERSITY, AUCKLAND, NEW ZEALAND

The World Manufacturing Congress '97 was organised jointly between Massey University and International Computer Science Conventions (ICSC) of Canada. The event was held from 18–21 November at Albany Campus, Massey University in Auckland, New Zealand. This inaugural WMC attracted the participation of over 30 nations and many aspects of manufacturing systems, manufacturing technology and manufacturing management were presented by high profile authors. WMC '97 was dedicated to Philip Crosby for his devotion to the field of quality and more specifically his ÒQuality is Free" impetus to the quality revolution in the late 70's.

FIFTH IFAC SYMPOSIUM ON ROBOTS CONTROL SYROCO '97 (3–5 SEPTEMBER 1997)

SYROCO '97 was the fifth of the IFAC series of triennial Symposia on Robot Control. Previous events were held in Barcelona (Spain), 1985; Karlsruhe (Germany), 1988; Vienna (Austria), 1991 and Capri (Italy), 1994. SYROCO '97 was held from September 3 to 5, 1997 in the “Cité des Congrès” in Nantes, France. The Chairman of the International Programme Committee was Bernard ESPIAU from INRIA Rhône Alpes (FRANCE); the Chairman of the National Organizing committee was Wisama KHALIL from IRCyN (Ecole Centrale de Nantes-FRANCE).

UNITED KINGDOM

29th ISR and Automation and Robotics '98

By IFR Vice Chairman and President of the B.R.A., Mike Wilson