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There is a growing tendency to use the Internet as the transmission medium of the telerobotic system since the Internet is inexpensive and available all over the world. However, the bilateral real-time teleroperation can be unstable due to the random time delays of the Internet. The `Event based teleoperation' is one of the fine approaches to overcome the random time delays. Since the event based control uses a non-time action reference, the stability and response performance of the system are affected by the time which an event is held for. This study introduces the variable holding time to secure stability and response performance at once. The proper holding time for each event is obtained depending on the characteristics of the task through the fuzzy logic. The proposed control scheme was implemented on a robot arm over the Internet to show its effectiveness.

It is known that existence of irregular transmission time delay is a major bottleneck for application of advanced robot control schemes to internet telerobotic systems. In the internet teleoperation system, the irregular transmission time delay causes a critical problem, which includes instability and inaccuracy. This paper suggests a practical internet teleoperation system with streaming buffer system, which consists of a buffer, a buffer manager, and a control timer. The proposed system converts the irregular transmission time delay to a constant. So, the system effectively transmits the control input to a remote site to operate a robot stably and accurately. This feature enables short control input intervals. That means the entire system has a large control bandwidth. The validity of the proposed method is demonstrated by experiments of teleoperation from USC (University of Southern California in U. S.A.) to HYU (Hanyang Univ. in Korea) through the Internet. The proposed method is also demonstrated by experiments of teleoperation through the wireless internet.

It was shown that the robustness of deterministic observers with respect to modeling errors, measurement bias and round-off errors can be represented by a single performance index, x 2 (P), the condition number of the observer eigenvector matrix. In this paper, based on the performance index, a robust observer design method is proposed for two-output systems where the observer gain can not be determined uniquely with respect to the desired observer poles. Utilizing the pole/zero locations of the observer dynamics, a step-by-step design procedure of the well-conditioned observer is developed. In addition, a new scaling method is developed with employing the eigenvector matrix as a scaling matrix. The proposed method is evaluated and compared with the Kalman filter technique in a spindle-drive simulation example where the load speed needs to be estimated based on the measured signals.

Optimal task sequence planning using a simulated annealing technique is developed for a high speed assembly station comprised of two robots. In order to minimize the tact time, parts are assembled by dual robots on moving workpieces which are transferred by a precision conveyer. The sequence of operations by the dual robots is optimized to minimize the tact time while avoiding the geometric and dynamic interferences between the dual robots. The optimization problem is a type of traveling salesman problem, but is highly complicated because the target destinations for placing individual parts keep moving on the conveyer. The speed of the conveyer which carries the workpieces should be also optimized in order to maximize the throughput of the assembly system. The task sequence optimization problem is formulated together with the problem of determining the conveyer speed. An efficient algorithm for the sequence optimization is developed and solved by the simulated annealing.

For an automated transportation system like PRT (Personal Rapid Transit) System or IVHS, an efficient vehicle-merging algorithm is required for smooth operation of the network. For management of merging, collision avoidance between vehicles, ride comfort, and the effect on traffic flow should be considered. This paper proposes an unmanned vehicle-merging algorithm that consists of two procedures. First, a longitudinal control algorithm is designed to keep a safe headway between vehicles in a single lane. Secondly, vacant slot and ghost vehicle' concept is introduced and a decision algorithm is designed to determine the sequence of vehicles entering a converging section considering total traffic flow. The sequencing algorithm is based on fuzzy rules and the membership functions are determined first by an intuitive method and then trained by a learning method using a neural net. The vehicle-merging algorithm is shown to be effective through simulations based on a PRT model.