An Improved Robot Path Planning Algorithm

Robot path planning is a NP problem. Traditionaloptimization methods are not very effective to solve it. Traditional genetic algorithm trapped into the local minimum easily. Therefore, based on a simple genetic algorithm and combine the base ideology of orthogonal design method then applied it to the population initialization, using the intergenerational elite mechanism, as well as the introduction of adaptive local search operator to prevent trapped into the local minimum and improvethe convergence speed to form a new genetic algorithm. Through the series of numerical experiments, the new algorithm has been proved to be efficiency.We also use the proposed algorithm to solve the robot path planning problem and the experiment results indicated that the new algorithm is efficiency for solving the robot path planning problems and the best path usually can be found

Direct Aerobic Carbonylation of C(sp2)-H and C(sp3)-H Bonds through Ni/Cu Synergistic Catalysis with DMF as the CO Source

The direct carbonylation of aromatic sp2 and unactivated sp3 C–H bonds of amides was achieved via nickel/copper catalysis under atmospheric O2 with the assistance of a bidentate directing group. The sp2 C–H functionalization showed high regioselectivity and good functional group compatibility. The sp3 C–H functionalization showed high site-selectivity by favoring the C–H bonds of α-methyl groups over those of the α-methylene, β- or γ-methyl groups. Moreover, this reaction showed a predominant preference for functionalizing the α-methyl over α-phenyl group. Mechanistic studies revealed that nickel/copper synergistic catalysis is involved in this process

3-D Laser-Based Multiclass and Multiview Object Detection in Cluttered Indoor Scenes

This paper investigates the problem of multiclass and multiview 3-D object detection for service robots operating in a cluttered indoor environment. A novel 3-D object detection system using laser point clouds is proposed to deal with cluttered indoor scenes with a fewer and imbalanced training data. Raw 3-D point clouds are first transformed to 2-D bearing angle images to reduce the computational cost, and then jointly trained multiple object detectors are deployed to perform the multiclass and multiview 3-D object detection. The reclassification technique is utilized on each detected low confidence bounding box in the system to reduce false alarms in the detection. The RUS-SMOTEboost algorithm is used to train a group of independent binary classifiers with imbalanced training data. Dense histograms of oriented gradients and local binary pattern features are combined as a feature set for the reclassification task. Based on the dalian university of technology (DUT)-3-D data set taken from various office and household environments, experimental results show the validity and good performance of the proposed method

A plane linkage and its tessellation for deployable structure

Deployable structures are widely used in space applications such as solar arrays and antennas. Recently, inspired by origami, more deployable structures have been developed. This paper outlined a novel design scheme for deployable structures by taking a plane linkage as an origami unit with a large deployable ratio. The mountain and valley (M-V) crease assignment and kinematics of the plane linkage were analyzed. Physical interference in the folding progress was discovered geometrically and resolved by the split-vertex technique. Finally, tessellation of the derived pattern was successfully used to create a large-deployable-ratio structure, which was found to exhibit considerable potential in future space applications

The Development of Biomimetic Spherical Hydroxyapatite/Polyamide 66 Biocomposites as Bone Repair Materials

A novel biomedical material composed of spherical hydroxyapatite (s-HA) and polyamide 66 (PA) biocomposite (s-HA/PA) was prepared, and its composition, mechanical properties, and cytocompatibility were characterized and evaluated. The results showed that HA distributed uniformly in the s-HA/PA matrix. Strong molecule interactions and chemical bonds were presented between the s-HA and PA in the composites confirmed by IR and XRD. The composite had excellent compressive strength in the range between 95 and 132 MPa, close to that of natural bone. In vitro experiments showed the s-HA/PA composite could improve cell growth, proliferation, and differentiation. Therefore, the developed s-HA/PA composites in this study might be used for tissue engineering and bone repair

Using an Ensemble of Incrementally Fine-Tuned CNNs for Cross-Domain Object Category Recognition

When the training data is inadequate, it is difficult to train a deep Convolutional Neural Network (CNN) from scratch with randomized initial weights. Instead, it is common to train a source CNN model on a very large data set beforehand, and then use the learned source CNN model as an initialization to train a target CNN model. In deep learning realm, this procedure is called fine-tuning a CNN. This paper presents an experimental study on how to combine a collection of incrementally fine-tuned CNN models for cross-domain and multi-class object category recognition tasks. A group of fine-tuned CNN models is trained on the target data set by incrementally transferring parameters from a source CNN model trained on a large data set initially. The last two fully-connected (FC) layers of the source CNN model are eliminated, and two New FC layers are added to make the learned new CNN model suitable for the target task. Based on Caltech-101 and Office data sets, the experimental results demonstrate the effectiveness and good performance of the proposed methods. The proposed method is more suitable for the object recognition task when there is inadequate target training data

A new controller design of electro-hydraulic servo system based on empirical mode decomposition

The signal of electro-hydraulic servo system is non-stationary and time-varying due to the influence of vibration, noise and mechanical impact. The traditional digital filter always suffers delay in time domain and the delay increases along with the increasing of frequency. Considering the features of electro-hydraulic servo system, the Hilbert-Huang transform method is an effective method to decompose the original signal and obtain the noise components. Some improvements are made based on Hilbert Huang transform method and a new real time on-line filtering method is proposed in this paper. This improved filter is able to decompose out the noise components and other interference components from original signal, and remove them off in real time. Based on this new on-line filter, a new controller is also designed. Compared the filtering result with the traditional digital filter, this new controller’s control performance is much better