Han-Pang Huang

Development of a myoelectric discrimination system for a multi-degree prosthetic hand

A multiple degrees of freedom prosthetic hand, NTU Hand, was developed in our laboratory. The paper focuses on the development of a myoelectric discrimination system for a multi-degree prosthetic hand. The discrimination system uses two surface electrodes to acquire the electromyography (EMG) signal from the flexor digitorum superficialis muscle and the extensor pollicis brevis muscle. Since eight types of hand movements, such as three-jaw chuck, lateral hand, hook grasp, power grasp, cylindrical grasp, centralized grip, flattened hand and wrist flexion are often used in daily life, they are used as key movements in the discrimination system. In order to distinguish those hand movements, the techniques of variance, bias zero-crossings, autoregressive model and spectral estimation are employed for preprocessing of features. Then, an error backpropagation neural network is applied to discriminate among the feature sets. Finally, an analysis interface system based on a PC environment is constructed to verify the idea. Besides, a 3-D graphic interface program based on the programmers hierarchical interactive graphic system (PHIGS) is applied to simulate the prosthetic movement of the NTU hand. The discrimination system can achieve a success rate of 85% for off-line test and of 71% for online test.

Time-optimal control for a robotic contour following problem

A mathematical formulation for the time-optimal contour following problem, defined by a unilaterally constrained manipulator, is presented. The formulation includes a careful development of the manipulator dynamics and of conditions for avoidance of impact between the end effector and the constraint surface. By a priori specification of the paths for the unconstrained motion segments, a parameterization approach is used to simplify the optimal control formulation, so that solution procedures can be identified. The methodology is applied to a simple contour-following problem for a planar Cartesian manipulator. >

EMG classification for prehensile postures using cascaded architecture of neural networks with self-organizing maps

Electromyograph (EMG) features have the properties of large variations and nonstationary issue in the classification of EMG is the classifier design. The major goal of this paper is to develop a classifier for the classification of eight kinds of prehensile postures to achieve high classification rate and reduce the online learning time. The cascaded architecture of neural networks with feature map (CANFM) is proposed to achieve the goal. The CANFM is composed of two kinds of neural networks: an unsupervised Kohonens self-organizing map (SOM), and a supervised multi-layer feedforward neural network. Experimental results show that by extracting EMG features, forth-order autoregressive model (ARM) and histogram of EMG signals (IEMG), as inputs, the proposed CANFM can obtain and remain high classification rates compared with other classifiers, including k-nearest neighbor method (K-NN), fuzzy K-NN algorithm, and back-propagation neural network (BPNN) in several online testing.

Dynamic visibility graph for path planning

In this paper, we propose a fast dynamic visibility graph (DVG) for constructing a reduced roadmap among convex polygonal obstacles. DVG is extracted from the global environment with the simple geometric method and rules. Moreover, the data preprocessing is based on the concept of V-circle. Through V-circle, the process is speeded up greatly. Finally, DVG is extended to deal with multi-target problems that traditionally require a lot of time for reconstructing configuration space (C-space).

Development and Fuzzy Control of a Pipe Inspection Robot

A new pipe inspection robot, called the National Taiwan University (NTU) Navigator, is described in this paper. The NTU Navigator is lightweight, modularly designed, and easily manipulated and repaired. The robot consists of camera, steering, driving, and functional mechanism modules. Each module has its own control circuit and functions. In addition, a new stretch mechanism is designed and optimized in order to adapt the robot to pipes of various radii. The robot can be easily controlled using GUI on a PC. A stable and smooth fuzzy steering controller for operating inside the pipes is constructed. The stability and performance of the fuzzy controller are shown and compared with both the conventional proportional-integral-derivative controller and the flatness-based controller. Simulations and experiments further justify the performance of the NTU Navigator.

A mobile robot that understands pedestrian spatial behaviors

In human society, there are many invisible social rules or spatial effects existing in our environments. The robot that does not comprehend these spatial effects might harm people or itself. This paper presents a spatial behavior cognition model (SBCM) to describe the spatial effects existing between people and people, people and environments. By understanding the spatial effects in human-lived environments, the robot not only predicts pedestrian intentions and trajectories but also behaves socially acceptable motions. Moreover, the concept of pedestrian ego-graph (PEG) is proposed to efficiently query pedestrian-like paths for trajectory prediction. Model evaluation and experiments are shown to verify the proposed idea in this paper.

Automatic EMG feature evaluation for controlling a prosthetic hand using supervised feature mining method: an intelligent approach

Electromyograph (EMG) has the properties of large variations and nonstationarity. There are two issues in the classification of EMG signals. One is the feature selection, and the other is the classifier design. Subject to the first issue, we propose a supervised feature mining (SFM) method, which is an intelligent approach based on genetic algorithms (GAs), fuzzy measure, and domain knowledge on pattern recognition. The SFM can find the optimal EMG feature subset automatically and remove the redundant from a large amount of feature candidates without taking trial-and-error. In the experiments, all feature candidates and optimal feature subset are conducted to demonstrate the validity of the proposed SFM. Moreover, experimental results show that the optimal EMG feature subset contained from SFM can obtain higher classification rates compared with using all feature candidates by K-NN method.

Mechanism design of a new multifingered robot hand

A new five-finger robot hand (NTU hand) with seventeen degrees of freedom (DOF) is developed in this paper. In contrast to traditional tendon-driven robot, the NTU hand has an uncoupled configuration such that each finger and joint are all individually driven. While all actuators, mechanical parts and sensors are packed on the hand, the size of NTU hand is almost the same as a human hand. Such compact design makes the hand easily adapt to industrial robot arms and prosthetic applications. According to the mechanical structure of the NTU hand, the direct and inverse kinematics are also developed in this paper.

Optimal layout and deployment for RFID systems

With increasing applications of RFID (Radio Frequency Identification) technology, reliability requirements for the deployment of RFID readers have become more critical. For a robust deployment of a RFID network, a systematic solution was proposed in this paper. To simplify the reader deployment problem, instead of the traditional 2D circle-like shape assumption, the ellipse/ellipsoid-like shape was taken to represent the signal range of an RFID antenna in this paper. Further, the performance of RFID was estimated statistically. In addition, a deployment tool was designed for users to obtain a recommended layout. For a given area, solutions of number and placement of RFID readers are computed fast and robustly. To avoid reader collision which may result in low efficiency of a RFID network, two simplified mechanisms were proposed. Finally, the practical implementation and simulations were performed to test the practicability of the deployment tool and further to confirm the robustness and adequacy of the proposed models.

Colored timed Petri net based statistical process control and fault diagnosis to flexible manufacturing systems

The quality consistence and machine utilization of a flexible manufacturing system (FMS) strongly depend on the statistical process control (SPC) and the correct fault diagnosis of equipment. An FMS can be modelled by the colored timed Petri net (CTPN). However, most CTPN models of FMS lack the activities of SPC and fault diagnosis, and they lead to incomplete FMS CTPN models. In this paper, the CTPN-based SPC and fault diagnosis models are proposed to model the FMS SPC and fault diagnosis behaviors. Since the models depend on the measured data from the inspection machines and the sensor data from the devices, the CTPN-based SPC and fault diagnosis models can be incorporated into the production CTPN models to give a complete model of FMS activities. It is shown that the CTPN-based fault diagnosis is easy to model, and the results are straightforward.