This paper presents a load management method based on OpenADR of smart grid. Previous demand side algorithm is restricted on reducing peak power. But, in this paper we suggest a method of performing the energy-saving control according to the power price utilizing building automatic control system installed on the customer side in the case of hourly differential pricing signal is transmitted to the open automated demand response system. And, we showed the integrated demand management software for 3 buildings.

The vehicle suspension system plays a very important part related with vehicle ride and handling. To improve the vehicle ride and handling many researches have been progressed from various damping parameter tuning techniques to the development of the electronic controlled suspension systems. In this paper, as one of the ride performance improvement a disturbance observer(DOB) based control system is applied to the quarter car vehicle model in order to show that the DOB can obtain good vibration isolation characteristics. First, the robust stability criterion for the DOB is introduced in detail, and then how DOB is applied to the 1/4 car vehicle model is represented, and finally to confirm the effectiveness of the DOB in vehicle ride performance improvement a computer simulation is carried out for various driving conditions.

This paper describes the design of a cellphone curved glass measuring device using by camera. The measuring device was composed of two camera, two backlight system, a body and so on, and the program was made for a camera calibration and noise removal, and also the program was made for height measurement of a cellphone curved glass using by subpixel algorism. And then a new technique for measuring the height of the cell phone curved glass was proposed. The characteristics test of height measurement of gage blocks and cell phone curved glasses was carried out, the error of the height measurement of gage block is less than ${\pm}0.005$ and the error of the height measurement of the cell phone curved glasses is less than ${\pm}0.005$. Thus it thought that the designed cellphone curved glass measuring device and the new technique for measuring the height was used to measure the height of the cellphone curved glass.

This paper introduces a tactilely transparent soft glove composed of soft materials and flexible structures. Although it is hard to achieve a high grasping force with conventional grip-assist gloves made from soft material, the proposed glove can exert a high force by using a novel structure. This structure has a triangular shape composed of flexible structural frames, soft fabric, and belts. It can produce grip-assist moment compliantly without harmful force or misalignment with the human fingers. The whole finger part that comes into contact with objects is made of thin and soft fabric in order to facilitate sensation transference. The proposed tactilely transparent soft glove enables the user to manipulate various objects owing to both the softness and high grasping force; it helps lifting heavy weight objects as well as permitting delicate tactile feeling on the palm and fingers. The proposed concept was applied to a two-finger grip-assist device for validation. In addition, the experimental results regarding grasping objects, fingertip force, and grasping force are presented.

The graph-based SLAM (Simultaneous Localization and Mapping) approach has been gaining much attention in SLAM research recently thanks to its ability to provide better maps and full trajectory estimations when compared to the filtering-based SLAM approach. Even though graph-based SLAM requires batch processing causing it to be computationally heavy, recent advancements in optimization and computing power enable it to run fast enough to be used in real-time. However, data association problems still require large amount of computation when building a pose graph. For example, to find loop closures it is necessary to consider the whole history of the robot trajectory and sensor data within the confident range. As a pose graph grows, the number of candidates to be searched also grows. It makes searching the loop closures a bottleneck when solving the SLAM problem. Our approach to alleviate this bottleneck is to sample a limited number of pose nodes in which loop closures are searched. We propose a heuristic for sampling pose nodes that are most advantageous to closing loops by providing a way of ranking pose nodes in order of usefulness for closing loops.

There is an increasing need for manufacturing systems to produce batches in small quantities. Such manufacturing systems are significantly difficult to develop with conventional automation equipment. Recently, several research groups have applied industrial dual-arm robots to cell production lines. A synchronization method for robots is necessary for the cell production process when robots work in a shared workspace. Conventional automation factories do not need this method because the main control system operates all of the machines or robots. However, our intended application for the developed robot is in small manufacturing environments that cannot install an expensive main control system. We propose an inexpensive and high-performance method with a simple digital in/out channel using a real-time communication protocol. The developed method was validated in a pilot production line for cellular phone packing.

This paper presents the implementation and control of a small-scaled excavator system. The commercial miniature of an excavator system has been modified and its control hardware is embedded to access the feedback control. Encoder sensors are attached to the joint and a force sensor is mounted on the end-effector so that feedback position control is accessible as well as force control. The dynamic model of the excavator system is derived as a four linkage robot arm and its control performances are simulated. Experimental studies of contact force control tasks are conducted to test the control algorithm for the excavator system.

An inventory control system was developed for multiproduct batch plants with an arbitrary number of batch processes and storage units. Customer orders are received by the plant at intervals and in quantities that are subject to random fluctuations. The objective of the plant operation is to minimize the total cost while maintaining inventory levels within the storage or warehouse capacity by adjusting the startup times, the quantities of raw material orders, and production batch sizes. An adaptive model-based control algorithm was developed that uses a periodic square wave model to represent the flows of material between the processes and the storage units. The effectiveness of this approach was demonstrated by performing simulations.

For the safe driving of autonomous vehicles, accurate position estimation is required. Generally, position error must be less than 1m because of lane keeping. However, GPS positioning error is more than 1m. Therefore, we must correct this error and a map matching algorithm is generally used. Especially, road marking intensity map have been used in many studies. In previous work, 3D LIDAR with many vertical layers was used to generate a local intensity map. Because it can be obtained sufficient longitudinal information for map matching. However, it is expensive and sufficient road marking information cannot be obtained in rush hour situations. In this paper, we propose a localization algorithm using an accumulated intensity local map. An accumulated intensity local map can be generated with sufficient longitudinal information using 3D LIDAR with a few vertical layers. Using this algorithm, we can also obtain sufficient intensity information in rush hour situations. Thus, it is possible to increase the reliability of the map matching and get accurate position estimation result. In the experimental result, the lateral RMS position error is about 0.12m and the longitudinal RMS error is about 0.19m.

As location recognition for autonomous vehicles develops, the need for a precise map for autonomous driving has increased. A precise map must be built based upon accurate position. Recent studies have accelerated research in this area by using various sensors that calculate the accurate position by comparing and recognizing objects around the roads. However, application of such methods is limited because these studies only take objects with significant verticality into consideration. Thus, new research is needed to overcome the limitations: a method that is not constrained by the existence of certain types of surrounding objects shall be proposed. Most roads contain road marking information, such as lanes, direction signs, and pedestrian crossings. Such information on the road surface is a valuable resource for building a precise map. This paper proposes a method of building a precise map by using road marking information.

Position of the vehicle for driving is essential to autonomous navigation. However, there appears GPS position error due to multipath which is occurred by tall buildings in downtown area. In this paper, GPS position error is corrected by using camera sensor and highly accurate map made with 3D-Lidar. Input image through inverse perspective mapping is converted into top-view image, and it works out map matching with the map which has intensity of 3D-Lidar. Performance comparison was conducted between this method and traditional way which does map matching with input image after conversion of map to pinhole camera image. As a result, longitudinal error declined 49% and complexity declined 90%.