It is necessary to estimate channel quality in order to put Bluetooth adaptive packet selection strategies into practice. However, the current Bluetooth channel quality estimation algorithms are either poor at timeliness or not applicable to systems which only support basic rate(BR) data packets(Gaussian frequency shift keying(GFSK) modulation scheme). It is investigated to apply the channel quality estimation algorithm based on power spectrum to Bluetooth adaptive packet selection strategies in this paper. Simulation results and analysis show that the proposed channel quality estimation algorithm based on power spectrum can achieve the accuracy less than 0.2 d B in the estimation range required by Bluetooth adaptive packet selection strategies. It has simple calculation and strong timeliness. The algorithm can also be suitable for different modulation schemes of Bluetooth data packets. It provides a good precondition for the achievement of Bluetooth adaptive packet selection strategies.
Support vector machines(SVMs) have been intensively applied in the domains of speech recognition, text categorization, and faults detection. However, the practical application of SVMs is limited by the non-smooth feature of objective function. To overcome this problem, a novel smooth function based on the geometry of circle tangent is constructed. It smoothes the non-differentiable term of unconstrained SVM, and also proposes a circle tangent smooth SVM(CTSSVM). Compared with other smooth approaching functions, its smooth precision had an obvious improvement. Theoretical analysis proved the global convergence of CTSSVM. Numerical experiments and comparisons showed CTSSVM had better classification and learning efficiency than competitive baselines.
An dynamic system for real-time obstacle avoidance path planning of redundant robots is constructed in this paper. Firstly, the inter-frame difference method is used to identify the moving target and to calculate the target area, then on the basis of color features and gradient features extracted from the target area, the feature fusion Cam-Shift mean shift algorithm is used to track target, improving the robustness of the tracking algorithm. Secondly, a parallel two-channel target identification and location method based on binocular vision is proposed, updating the target’s three-dimensional information in real time. Then, a dynamic collision-free path planning method is implemented: the safety rods are removed through the intersection test, and the minimum distance is derived directly by using the coordinate values of the target in the local coordinate system of the rod. On this basis, the obstacle avoidance gain and escape velocity related to the minimum distance is established, and obstacle avoidance path planning is implemented by using the zero space mapping matrix of redundant robot. Experiments are performed to study the efficiency of the proposed system.