Wireless power transfer (WPT) is one solution to realize long flight times and accommodate various missions of micro-uncrewed aerial vehicles (MAVs). Reducing the constraint of power transmission distance and realizing high beam efficiency are possible because of the high directivity of WPT using millimeter wave (MMW) methods. Nevertheless, no report of the relevant literature describes an investigation of sending power to an MAV using MMW because MMW rectennas have low efficiency. The purpose of our study is to conduct fundamental research of a high-efficiency and high-power rectenna at 94 GHz aimed at MAV application using MMW. As described herein, we developed and evaluated a 100-mW-class single-diode rectifier at 94 GHz with a finline of a waveguide (WG) to a microstrip-line (MSL) transducer. With the optimum load of 150 Ω at input power of 128 mW, the output DC power and rectifying efficiency were obtained respectively as 41.7 mW and 32.5%. By comparison to an earlier study, measurement of 94 GHz rectifiers under high power input becomes more accurate through this study.

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This paper discusses the compensation of tool paths for machining flexible parts. Despite various research published on the topic, machining in practice nowadays remains limited to tool path planning based on only the geometric models of the parts and tools. This is mainly because that tool path compensation methods usually require accurate physical information of the systems and rely on analytical or finite element simulations, which are often not available to the end-users. In regards to this problem, this paper presents data-oriented nonparametric learning methods that require solely the geometric measurements of the trial machined contour(s). The physical parameters of the parts and tools as well as simulations of the machining process are not required. Two algorithms are developed based on Gaussian Process Regression and Artificial Neural Network respectively. Experimental tests are conducted. A plan of further improving the results using an auxiliary real-time vision sensor is also discussed.

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