Power line inspection is essential work for the maintenance of electric grids. Besides manually inspecting power lines, which is still the main method, helicopters are also used for the inspection from the sky. In the recent years, unmanned flying systems were used for power line inspection in order to reduce the risk. In this paper, the design and application of SmartCopter, an unmanned autonomous helicopter based inspection robot, are described, including the design of flight control, inspection system, safe distance design, ground station, inspection mode, etc. Some inspection results are presented as well.
In this paper, a new approach based on the q-method for coarse alignment is presented. Compared with the standard approach which is based on determining DCM (direct cosine matrix), the new method can avoid solving the DCM and get the initial quaternion directly that we used for the navigation calculation.
There are many constraints in the motion of a ground target, for example, geographic constraints. So it is complicated to track a ground target. However, meanwhile, geographic constraints are a sort of information. How to apply these information properly is a worthy problem to study. For maneuvering ground targets, constrained multiple model Gaussian mixture probability hypothesis density (CMM-GMPHD) filter is proposed in this paper. Model conditioned distribution and model probability are used in the proposed CMM-GMPHD filter. In the proposed method, the Gaussian component in the GM-PHD filter is estimated by multiple model method, and the final results of the Gaussian components in PHD of maneuvering ground targets are the fusion of multiple model estimations. In addition, the road information is described as equality constraints and then it is used to correct the estimated state in the method. The simulation results indicate that the proposed algorithm can track the maneuvering ground targets steadily in the environment of clutter.
A method for estimating AR model parameters and power spectrum of vehicle audio signals was introduced. Three layer with recessive neuron as linear transfer function in artificial neural network was used in the paper. Experiment proved that the AR model parameters and power spectrum of vehicle audio signals estimated by the method of artificial neural networks can get the same result as Burg algorithm. This result showed that the method of artificial neural networks was effective.
The dynamic system, i.e., gradient dynamic system (GDS), is theoretically designed by defining a square-based nonnegative or at least lower-bounded error-monitoring function, which is termed the energy function (EF). Such a dynamic system is then cast in the form of a first-order differential equation. To compute scalar square roots, in this paper, different square-based nonnegative EFs, which lead to different GDS models, are proposed and developed as the error-monitoring functions. Towards the final purpose of field programmable gate array (FPGA) and application-specific integrated circuit (ASIC) realization, the MATLAB Simulink modeling and verification of such different GDS models are further investigated for the computation of scalar square roots. The modeling results with two illustrative examples substantiate the efficacy of the proposed GDS models for scalar square roots computing.
