This paper presents a new developed multisensory five-fingered dexterous robot hand : the DLR/HIT Hand II. The hand has an independent palm and five identical modular fingers, each finger has three DOFs and four joints. All the actuators and electronics are integrated in the finger body and the palm. By using powerful super flat brushless DC motors, tiny harmonic drivers and BGA form DSPs and FPGAs, the whole finger's size is about one third smaller than the former finger in the DLR/HIT Hand I. By using the steel coupling mechanism, the phalanx distal's transmission ratio is exact 1:1 in the whole movement range. At the same time, the multisensory dexterous hand integrates position, force/torque and temperature sensors. The hierarchical hardware structure of the hand consists of the finger DSPs, the finger FPGAs, the palm FPGA and the PCI based DSP/FPGA board. The hand can communicate with external with PPSeCo , CAN and Internet. Instead of extra cover, the packing mechanism of the hand is implemented directly in the finger body and palm to make the hand smaller and more human like. The whole weight of the hand is about 1.5Kg and the fingertip force can reach 10N.

No abstract

No abstract

No abstract

No abstract

Oversegmentation is a major drawback of the morphological watershed algorithm. Here, we study and reveal that the oversegmentation is not only because of the irregular shapes of the particle images, which people are familiar with, but also because of some particles, such as ellipses, with more than one centre. A new parameter, the striping level, is introduced and the criterion for striping parameter is built to help find the right markers prior to segmentation. An adaptive striping watershed algorithm is established by applying a procedure, called the marker searching algorithm, to find the markers, which can effectively suppress the oversegmentation. The effectiveness of the proposed method is validated by analysing some typical particle images including the images of gold nanorod ensembles.

Abstract-Several practical issues associated with achieving effective impedance performance in the finger joint space and stable grasping on a five-fingered dexterous hand are investigated in this work. A Multiprocessor structure based on field programming gate array (FPGA) is proposed to realize the high-level hand impedance controller. The key feature of the hardware system is a dual-processor architecture based controller, one of which is used for data communication control and the other for joint and object level control. High speed Experimental results and simulation with a five-fingered dexterous robot hand demonstrate that the controller architecture is able to achieve the desired robot hand impedance control performance and effective stable grasping.

Parkinson's diagnosis through voice analysis (PDVA) has been attracting increasing attention. In this paper, the influence of sampling rate on PDVA is studied. By analyzing the main difficulties that hamper the development of PDVA, the significance of seeking guidelines on sampling rate is discussed. Then voices from both healthy controls and patients with Parkinson's disease are recorded, for which the sampling rate used is given special consideration. Recordings of other sampling rates are generated via down sampling the recorded voices. Then it is proposed to adopt six metrics from four levels to assess the impacts of sampling rate, which are information entropy, reconstruction error, feature correlation, classification accuracy, computational cost, and the storage cost. Through extensive experiments, basic guideline to seek an appropriate sampling rate is provided. It is concluded that a sampling rate of 96 kHz is preferred when no limits of storage and computational costs are imposed. However, a lower sampling rate may be needed if the storage size and computational complexity are the main concerns.