Early studies on robot machining were reported in the 1990s. Even though there are continuous worldwide researches on robot machining ever since, the potential of robot applications in machining has yet to be realized. In this paper, the authors will first look into recent development of robot machining. Such development can be roughly categorized into researches on robot machining system development, robot machining path planning, vibration/chatter analysis including path tracking and compensation, dynamic, or stiffness modeling. These researches will obviously improve the accuracy and efficiency of robot machining and provide useful references for developing robot machining systems for tasks once thought to only be capable by CNC machines. In order to advance the technology of robot machining to the next level so that more practical and competitive systems could be developed, the authors suggest that future researches on robot machining should also focus on robot machining efficiency analysis, stiffness mapbased path planning, robotic arm link optimization, planning, and scheduling for a line of machining robots.

In this paper the covering-blanket method widely used to estimate fractal dimension is improved. The D-dimensional area K, which has never been detailed in previous references, is clarified and further extended to a fractal signature as a function of scale and space. After defming two discrepancy measurements of multiscale fractal signature, an algorithm of man-made target detection, which is based on fractal signature change, is presented and tested on looking-forward infrared images collected by long wave infrared camera on sea surfaces. The results of using the D-dimensional area are compared with those of using the fractal dimension, and suggest that the proposed method performs better in detecting ship targets embedded in natural scenes.

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