ADVANCES IN AUTOMATION

1.Miniature machines

Cambridge UK scientists are attempting to cut groves in silicon chips just wide enough to contain one molecule of DNA. If successful it would mean that a hand-held device using such chips could be programmed to read the entire sequence of human DNA. Such computers could, for example, be built to identify causes of any sudden infectious diseases with a diagnosis obtained in minutes rather than in the days it could take using present-day technology. The report of these researches suggests that the whole process could then be a more controlled one with the readings taken being more precise. A comparison with current channel cutting methods was also given. Apparently, channels in a chip are normally cut to a measure of millionths of a metre, whilst the Cambridge researchers are now down to 100 millionth of a metre and confidently hope to achieve 10 billionths of a metre.

This paper addresses the kinematic modelling, solutions and trajectory planning of a tele-laparoscopic manipulator. This type of manipulator can be used in remote positioning of laparoscopic tools through tele-operating system. Specifically the paper models kinematics of a typical manipulating system which can be used in such tele-surgery. Inverse kinematics solutions are also obtained for two kinematically constraint motions which are part of a typical trajectory of the laparoscopic tools. These are fixed axis rotation of the tool and its straight line motion. Simulation results are presented to demonstrate the validity of such models and solutions.

NASA has developed a free-flying camera known as AERCam to assist Space Shuttle and Space Station operations. The first AERCam vehicle was controlled from within the Space Shuttle using a hand-held controller. We have developed a system for controlling AERCam remotely from the ground, which involves significant communication delays. We have tested its use with NASA's AERCam dynamics simulation in place of the actual vehicle. Our ground system uses a predictive display1 that is based on a similar simulation of Shuttle and AERCam dynamics. For both physical and numeric reasons, the behavior of the remote vehicle may drift from what is expected by the predictive display system. We have developed a mechanism to periodically re-establish correspondence of the ground simulation with the remote vehicle using tracking data that reports AERCam's recent behavior. Our system also provides a basis for future development of more advanced autonomous ground control for space vehicles such as AERCam.

In this paper we propose a tracking adaptive impedance controller for robots with visual feedback. It is based on a generalized impedance concept where the sensed distance is introduced as a fictitious force to the control in order to avoid obstacles in restricted motion tasks. The controller is designed to compensate for full non-linear robot dynamics. Robot parameters adjustment is introduced to reduce the sensibility of the controller design to dynamic uncertainties of the robot and the manipulated load. It is proved that the vision control errors are ultimately bounded in the image coordinate system. Simulations are carried out to evaluate the controller performance.

Fuzzy control has been widely applied in industrial controls and domestic electrical equipment. The automatic learning of fuzzy rules is a key technique in fuzzy control. In this paper, a software development system for fuzzy control is presented. Since the learning of fuzzy rules can be seen as finding the best classifications of fuzzy memberships of input-output variables in a fuzzy controller, it can also be seen as the combination optimization of input-output fuzzy memberships. Multi-layer feedforward network and genetic algorithms (GA) can be used for the automatic learning of fuzzy rules. The algorithms and their characteristics are described. The software development system has been successfully used for the design of some fuzzy controllers.

Manipulability ellipsoids are effective tools to perform task space analysis of robotic manipulators in terms of velocities, accelerations and forces at the end effector. In this paper a new definition of a dynamic manipulability ellipsoid for redundant manipulators is proposed which leads to more correct results in evaluating manipulator capabilities in terms of task-space accelerations. The case of manipulators in singular configurations is also analyzed. Two case studies are presented to illustrate the correctness of the proposed approach.

The focus of this work is on sensor-based motion planning for a biped robot operating in a scene with unknown obstacles. Using on-line sensor information about its surroundings, the robot negotiates obstacles on its way. Depending on the obstacle's shape, size, and location, the decision-making system chooses an appropriate walking pattern. The robot then negotiates the obstacle and resumes stable motion. The walking pattern is chosen from a small number of precomputed patterns that together cover a reasonably wide range of possible situations. The overall control strategy is based on the concept of Zero Moment Point. Each precomputed pattern guarantees dynamically stable motion; its stability is obtained by adjusting the swing leg center of mass and hip position trajectories. The approach is fast enough for real-time implementation. Simulation experiments demonstrate stability of motion when negotiating various obstacles.

One of the important issues of walking machine active force control is a successful distribution of the body force to the feet to prevent leg slippage. In this paper, a new force distribution method, the Friction Constraint Method (FriCoM), is introduced. The force distribution during the walking of a typical quadruped crawl gait is analyzed by using the FriCoM. Computation results show that the distributed forces of the feet are continuous during the walking. This reflects the change of the force distribution during actual conditions. The comparison with a pseudo-inverse method shows that the FriCoM is more practical. The FriCom also requires less computation time than that by an incremental optimization method. Some problems, such as the singularity in the application of the FriCoM, are discussed. The FriCoM will be used in the active force control of a quadruped robot that is taken as a platform for the research on the study of terrain adaptation.

This paper introduces a new approach to robust path planning for mobile robots entirely based on information from environment perception sensors. This method avoids the use of odometry which leads to the accumulation of errors resulting from the robot's position computing. We proceed as follows: we create regions inside which the robot detects the same obstacle segments. A node graph represents all the regions and their links. Then a planning algorithm is used to find a path which joins a start to a goal region. The final stage consists in applying a robust robot motion control as regards the uncertainties of the environment model. This approach contributes to a control system for indoor robots which is environment referenced. The sensors we deal with are first a continuous laser or ultrasonic scanning system, then a discrete ultrasonic belt whose limits of use we show.

Although robots have some kinematic and dynamic constraints such as the limits of the position, velocity, acceleration, jerk, and torque, they should move as fast as possible to increase the productivity. Researches on the minimum-time trajectory planning and control based on the dynamic constraints assume the availability of full dynamics of robots. However, the dynamic equation of robot may not often be exactly known. In this case, the kinematic approach for the minimum-time trajectory planning is more meaningful. We also have to construct a controller to track precisely the minimum-time trajectory. But, finding a proper controller is also difficult if we do not know the explicit dynamic equations of a robot.

This paper describes an optimization of trajectory planning based on a kinematic approach using the evolution strategy (ES), as well as an optimization of a sliding mode tracking controller using ES for a robot without dynamic equations.

A fast numerical procedure is presented for computing growth distances between a pair of polytopes in three dimensional space that move incrementally along specified smooth paths. The procedure carrys out the growth distance evaluations efficiently by predicting and verifying contact configurations between a pair of grown polytopes. In the prediction and verification the procedure uses vertex and facial characterizations of polytopes and exploits their geometric adjacency information. The computation time, in average, is very small and does not depend significantly on the geometric complexity of two polytopes. A numerical example is presented to demonstrate the applicability of the procedure to interference detection in robotic simulations.

This paper evaluates the influence of target location on robot repeatability. An experiment was set up to analyze the effect of the three-dimensional target location on robot repeatability. An error-analysis model to determine repeatability based on the robot's kinematic model and known robot parameters was developed. Experimental results indicated that there was a significant statistical difference between repeatability at different locations in the workspace and that the height of the target point influenced repeatability. Experimental results tended to those derived from the error-analysis kinematic model. Hence, to determine the optimal target location, there is no need for extensive experimentation; instead, only a few target points can be sampled and compared to an error-analysis model.