The IEEE 802.11p/1609 standards specify a suite of communication protocols for vehicular communication networks. A new operational mode, called the WAVE (Wireless Access in Vehicular Environments) mode, is defined to enable communication among high-speed vehicles or between a vehicle and a roadside infrastructure network. In the WAVE mode, a mobile/stationary station uses a combined FDMA/TDMA channel access scheme to switch its channel between the control channel and a service channel every 50 ms. The primary purpose of this design is to detect new services announced by other stations. However, it a station would like to use all of its service channel bandwidth to transmit a large volume of data to another station, switching back to the control channel every 50 ms without doing anything useful only unnecessarily reduces the maximum possible transmission throughput by a half. To overcome this problem, in this paper we propose an improved channel access scheme to allow a station to stay on a service channel as long as it requires before returning to the control channel. Our simulation results show that the proposed scheme significantly improves the service channel utilization under various network conditions.

In this paper, we present an integrated simulation platform, called NCTUns, for vehicular traffic, communication, and network researches. This platform combines the capabilities supported by a network simulator and those supported by a traffic simulator. With these simulation capabilities, NCTUns can be used to design protocols for intelligent transportation systems (ITS) communication networks such as a wireless vehicular communication network. Besides, the novel architecture of the platform enables the real-world Linux protocol stack and any real-world application to be used in simulations of such networks. In this paper, we present the design of NCTUns for supporting ITS researches and show its scalability.

Mobile robots frequently replace humans in handling and transporting wafer carriers in semiconductor production lines. A mobile robot is constructed in this paper. The developed mobile robot is primarily composed of a mobile base, a robot manipulator, and a vision system. Since the guidance control system of the mobile base inevitably causes positioning errors of the mobile base, this study employs the eye-in-hand vision system to provide visual information for controlling the manipulator of the mobile robot to grasp accurately stationary material during pick-and-place operations between a predefined station and the mobile robot. This work further proposes a position-based look-and-move task encoding control strategy for eye-in-hand vision architecture, that maintains all target features in the camera's field of view throughout the visual guiding. Moreover, the manipulator can quickly approach the material and precisely position the end-effector in the desired pose. Numerous techniques are required for implementing such a task, including image enhancement, edge detection, corner and centroid detection, camera model calibration method, robotic hand/eye calibration method, using a camera with controlled zoom and focus, and task encoding scheme. Finally, the theoretical results for the proposed control strategy are experimentally verified on the constructed mobile robot. Specific experimental demonstrations include grasping the target object with different locations on the station and grasping the target object tilted by different angles to the station.

The characteristics of a knowledge-based control strategy that support dynamic stability in a walking machine are discussed. A generalized set of solutions is optimized through simulation, and tabulated in an organized way for real-time use. Once properly evoked, the generalized solutions are modified on the basis of, sensory input. The result is a faster, less complex and adaptive control process. This work is part of a larger research effort centered on autonomous motion of bipeds.>