International Journal of Intelligent Engineering and Systems

6

Authors: Longxin Lin, Haijun Xu, Haibin Xie, Lincheng Shen

Bionic underwater robot is a new-type underwater robot which propelled and controlled by several bionic fins. Heaving motion is an indispensably function for most bionic underwater robots. Bionic bladder system is an apparatus which can realize both heaving and pitching control. It was inspired by biologic fish’s bladder. It was composed of a cylinder, a piston, a pipe, a rolling guide, two ball screws and two servomotors. The dynamic models of the bionic bladder system for heaving and pitching motion were established and based on which a dual-velocity control system was designed. Two control channels realized decoupling by setting different control cycles, and a PID controller are designed for each control channel. Simulations with the real design parameters and different control cycles were performed. Results indicated that the bionic bladder system can get a good control performance with proper control parameters.

7

Authors: Huahua Chen, Xueyi Ye

3D map building is an important task of autonomous land vehicle(ALV) for obstacle detection, path planning. This paper analyzes the defects of the traditional 3D map building method, and then proposes a novel method based on projection of virtual height line(PVHL). The method projects virtual height line(VHL) into the stereo vision system by transforming the world coordinate of each point on VHL into its image coordinate, and generates two projection lines(PLs) in two images. On the two PLs, only the correspondence that is the projection of the intersection point of VHL and the surface of the scene has the maximum similarity metric. Then finding the height of the scene point is equivalent to proving whether the real correspondence of VHL has the maximum similarity metric or not. Experiments show that the proposed method is effective. And compared with that of the traditional, the results show that the proposed avoids unnecessary computation time and has better performance than the traditional, and can build the interested region only.

9

Authors: R A. Raja Mahmood , A H. Muhamad Amin , and A. I. Khan

A lightweight, fast and efficient pattern classifier based on Distributed Hierarchical Graph Neuron (DHGN) is proposed and implemented. A classifier with such features is essential for the emerging networks such as wireless sensor networks and mobile ad hoc networks, where resources such as bandwidth and energy are limited. The proposed classifier adopts an in-network processing algorithm and has a one cycle learning capability. DHGN network is a new form of neural networks which consist of a hierarchical graph-based representation of input patterns. This paper compares the proposed solution with the well known Self-Organizing Map (SOM) classifier, in relation to accuracy and computational complexity. The results show that our solution offers lower computational complexity than SOM while guaranteeing satisfactory accuracy.