International Journal of Information Acquisition

A Complementary Metal Oxide Silicon (CMOS) optical micro-radiator vacuum sensor has been designed, tested and calibrated. The package is comprised of a micromachined radiator and a photodetector. The sensitivity improvement of the system over the conventional Pirani gauge is up to nine magnitudes depending on the operating power of the micro-radiator. To increase sensor's dynamic range, an automated power-switching system has been demonstrated for pressure sensing operated with constant photodetector output. Calibration of the system has been performed by comparison with secondary standards. Experimental results showed that the sensor's measurement range from 10^-3Pa to 10⁵Pa has been achieved as its relative error is less than 8%.

For dexterously performing object grasping and manipulation with multifingered hand of robot, sensing the fingertip forces with high-sensitivity and high-stiffness is desired. In general, based on previous sensing structures, we have to reduce a sensor's stiffness for obtaining a higher sensitivity of the sensor. It is hard to realize the force sensing with both of high-sensitivity and high-stiffness by previous sensing structures. This paper proposes a novel mechanism called Strain-Deformation Expansion Mechanism for 3-axis force sensing. By the force sensing mechanism, the small strain-deformation used for force sensing can be expanded while the sensor stiffness will not be reduced but will be heightened. In this paper, the force sensing principle is addressed by analyzing the deformation of the sensing mechanism and the forces acting on the sensor theoretically. Then, the sensitivity of the sensing mechanism and its expansion rate of sensitivity are defined, and a design method for realizing the sensing mechanism with high sensitivity is discussed. Lastly, some experiments are performed to show the basic characteristics and the effectiveness of the sensing mechanism.

In order for a service robot to approach humans and provide the services it has been designed for, an efficient system for people tracking and identification must be developed. This paper presents a novel solution to the problem that makes use of different sensors and data fusion techniques. The robot utilizes a laser device and a PTZ color camera to detect, respectively, human legs and faces. The relative information is integrated, in real-time, using a sequential implementation of Unscented Kalman Filter. Furthermore, thanks to an histogram comparison with a measure based on the Bhattacharyya coefficient, people are also identified and labelled according to their clothes. This measure is also used to improve the robustness of the data association process. The effectiveness of the proposed method is shown by experiments with a real mobile robot in challenging situations.

Time-to-contact (TTC) provides vital information for obstacle avoidance and for the visual navigation of a robot. In this paper, we present a novel method to estimate the TTC information of a moving object for monocular mobile robots. In specific, the contour of the moving object is extracted first using an active contour model; then the height of the motion contour and its temporal derivative are evaluated to generate the desired TTC estimates. Compared with conventional techniques employing the first-order derivatives of optical flow, the proposed estimator is less prone to errors of optical flow. Experiments using real-world images are conducted and the results demonstrate that the developed method can successfully achieve TTC with an average relative error (ARVE) of 0.039 with a single calibrated camera.

This paper proposes a new objective, non-reference quality metric for evaluating the performance of pixel-level image fusion. The metric is designed on a likelihood function for color cue that measures the similarity of color- or grey-level distributions. We have provided a theoretical analysis on how the quality metric responds to weighted averaging fusion algorithm. Then the slide window is used to calculate the metric over local region with the weight which is assessed by local saliency and indicates the relative importance. Extensive experiments have demonstrated that the metric is more effective and consistent with subjective evaluations compared with other metrics.

This paper proposes a method for topologically visualizing the perceptual information of a partner robot. First, we explain the methods for human detection, human motion extraction, and object recognition. Next, we explain the perceptual system of the robot based on the detected human and objects. We propose a topological visualization method based on a spring-mass-damper system according to the perceptual information. Finally, we show several experimental results of the proposed method, and the proposed method enables a human to understand what the robot perceives in the interaction with the human and environment.

Vision-based sensors are a key component for robot-systems, where many tasks depend on image data. Realtime control constraints bind a lot of processing power for only a single sensor modality. Dedicated and distributed processing resources are the "natural" solution to overcome this limitation. This paper presents experiments, using embedded processors as well as dedicated hardware, to execute various image (pre)processing tasks. Architectural concepts and requirements for intelligent vision systems have been acquired.

Continuing advances in virtual reality (VR) technology with respect to the new addition of force and touch feedbacks have enhanced VR realism and led to the development of many useful and accessible VR systems. One of the emerging research fields is in rehabilitation training. This paper introduces a virtual reality-based hand manipulation training system with three applications: virtual writing, virtual painting and virtual dialing. The system is mainly for training hand movement precision, speed, force, and direction control. A haptic device — PHANTOM Premium 1.0 is used to give the user immediate force feedbacks to feel immersed in the virtual environment during the training session. A new collision detection method is developed for accurate and rapid calculation of the interaction between the haptic and virtual environments. The implementation performances are calculated and given to the user in real time. The practicing results are also saved for evaluation and supervision by the specialist.

In this paper, robust control of the decentralized guaranteed cost was studied for a class of complex network with impulsive effects and nonlinear perturbation. Based on the Lyapunov stability theorem, sufficient conditions for the decentralized guaranteed cost controllers were obtained. The design method of the decentralized guaranteed cost control law was given by solving a parameter-dependent Riccati matrix equation. An example is given to illustrate the effectiveness of the presented scheme.