Informed anytime fast marching tree for asymptotically-optimal motion planning

In many applications, it is necessary for motion planning planners to get high-quality solutions in high-dimensional complex problems. In this paper, we propose an anytime asymptotically-optimal sampling-based algorithm, namely Informed Anytime Fast Marching Tree (IAFMT*), designed for solving motion planning problems. Employing a hybrid incremental search and a dynamic optimal search, the IAFMT* fast finds a feasible solution, if time permits, it can efficiently improve the solution toward the optimal solution. This paper also presents the theoretical analysis of probabilistic completeness, asymptotic optimality, and computational complexity on the proposed algorithm. Its ability to converge to a high-quality solution with the efficiency, stability, and self-adaptability has been tested by challenging simulations and a humanoid mobile robot

Stereo Dense Scene Reconstruction and Accurate Localization for Learning-Based Navigation of Laparoscope in Minimally Invasive Surgery

Objective: The computation of anatomical information and laparoscope position is a fundamental block of surgical navigation in Minimally Invasive Surgery (MIS). Recovering a dense 3D structure of surgical scene using visual cues remains a challenge, and the online laparoscopic tracking primarily relies on external sensors, which increases system complexity. Methods: Here, we propose a learning-driven framework, in which an image-guided laparoscopic localization with 3D reconstructions of complex anatomical structures is obtained. To reconstruct the 3D structure of the whole surgical environment, we first fine-tune a learning-based stereoscopic depth perception method, which is robust to the texture-less and variant soft tissues, for depth estimation. Then, we develop a dense visual reconstruction algorithm to represent the scene by surfels, estimate the laparoscope poses and fuse the depth maps into a unified reference coordinate for tissue reconstruction. To estimate poses of new laparoscope views, we achieve a coarse-to-fine localization method, which incorporates our reconstructed 3D model. Results: We evaluate the reconstruction method and the localization module on three datasets, namely, the stereo correspondence and reconstruction of endoscopic data (SCARED), the ex-vivo phantom and tissue data collected with Universal Robot (UR) and Karl Storz Laparoscope, and the in-vivo DaVinci robotic surgery dataset, where the reconstructed 3D structures have rich details of surface texture with an accuracy error under 1.71 mm and the localization module can accurately track the laparoscope with only images as input. Conclusions: Experimental results demonstrate the superior performance of the proposed method in 3D anatomy reconstruction and laparoscopic localization. Significance: The proposed framework can be potentially extended to the current surgical navigation system

Hand Motion Classification Using a Multi-Channel Surface Electromyography Sensor

The human hand has multiple degrees of freedom (DOF) for achieving high-dexterity motions. Identifying and replicating human hand motions are necessary to perform precise and delicate operations in many applications, such as haptic applications. Surface electromyography (sEMG) sensors are a low-cost method for identifying hand motions, in addition to the conventional methods that use data gloves and vision detection. The identification of multiple hand motions is challenging because the error rate typically increases significantly with the addition of more hand motions. Thus, the current study proposes two new methods for feature extraction to solve the problem above. The first method is the extraction of the energy ratio features in the time-domain, which are robust and invariant to motion forces and speeds for the same gesture. The second method is the extraction of the concordance correlation features that describe the relationship between every two channels of the multi-channel sEMG sensor system. The concordance correlation features of a multi-channel sEMG sensor system were shown to provide a vast amount of useful information for identification. Furthermore, a new cascaded-structure classifier is also proposed, in which 11 types of hand gestures can be identified accurately using the newly defined features. Experimental results show that the success rate for the identification of the 11 gestures is significantly high

Evaluation and Analysis Model of Wine Quality Based on Mathematical Model

This paper takes wine quality evaluation as the research object, establishes the analysis and evaluation model of wine quality, and explores the influence of physical with chemical indicators of wine grapes and wine on the wine quality. Firstly, the Mann-Whitney U test is used to analyze the wine evaluation results of the two wine tasters, and it is found that the significant difference between the two is small. Then this paper uses the Cronbach Alpha coefficient method to analyze the credibility of the two groups of data. It is found that the credibility of the first group of wine scores is significantly greater than that of the second group and the white wine scores are more reliable than the red wine. Therefore, the first set of data and white wine can be applied for follow-up studies. Next, the principal component analysis is used to extract the main indicators and calculate the factor coefficients as the Ward method in cluster analysis is used to classify the wine into four grades according to the quality score of the wine. Then, based on the extracted principal components that is physical with chemical indicators, this paper does the multiple linear regression analysis of wine quality, and takes the influence of aromatic substances on the aroma of wine in physical with chemical indicators as an example. Regression analysis shows that there is a positive correlation linear relationship between the scores of the aroma of wine and C2H6O, C6H12O2, C3H8O, C11H24, C7H12O2, C5H10O2 and C10H16. It can be judged that the aromatic substances in the wine such as C2H6O have a regular influence on the odor of the wine, and it is inferred that other physical and chemical properties have a similar regular relationship with the wine quality. This provides an effective reference for the analysis and evaluation of wine quality by using physical with chemical indicators such as aromatic substances in wine in the future

Ground beetle assemblages in Beijing’s new mountain forests

Mature forests have been almost completely destroyed in China’s northern regions, but this has been followed by large-scale reforestation in the wake of environmental degradation. Although future forest plantations are expected to expand over millions of hectares, knowledge about the ecology and biodiversity of China’s replanted forests remains very limited. Addressing these knowledge gaps, we recorded ground beetle (Coleoptera: Carabidae) communities in five secondary forest types: plantations of Chinese Pine (Pinus tabulaeformis) and Prince Rupprecht’s Larch (Larix principis-rupprechtii), Oak (Quercus wutaishanica) and Asian White Birch (Betula platyphylla) woodlands, and naturally regenerated mixed forest. Species richness peaked in mixed forests, while pine and oak woodlands harboured discrete communities of intermediate species richness. Oak, pine and mixed forest habitats also showed high levels of species turnover between plots. Canopy closure was an important factor influencing ground beetle assemblages and diversity, and a number of forest specialist species only occurred in pine or oak forests. We believe that some forest specialists have survived earlier deforestation and appear to be supported by new plantation forests, but maintenance of secondary native oak and mixed forests is crucial to safeguard the overall species pool

Biologically inspired robotics

Robotic engineering inspired by biology—biomimetics—has many potential applications: robot snakes can be used for rescue operations in disasters, snake-like endoscopes can be used in medical diagnosis, and artificial muscles can replace damaged muscles to recover the motor functions of human limbs. Conversely, the application of robotics technology to our understanding of biological systems and behaviors—biorobotic modeling and analysis—provides unique research opportunities: robotic manipulation technology with optical tweezers can be used to study the cell mechanics of human red blood cells, a surface electromyography sensing system can help us identify the relation between muscle forces and hand movements, and mathematical models of brain circuitry may help us understand how the cerebellum achieves movement control. Biologically Inspired Robotics contains cutting-edge material—considerably expanded and with additional analysis—from the 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO). These 16 chapters cover both biomimetics and biorobotic modeling/analysis, taking readers through an exploration of biologically inspired robot design and control, micro/nano bio-robotic systems, biological measurement and actuation, and applications of robotics technology to biological problems. Contributors examine a wide range of topics, including: A method for controlling the motion of a robotic snake The design of a bionic fitness cycle inspired by the jaguar The use of autonomous robotic fish to detect pollution A noninvasive brain-activity scanning method using a hybrid sensor A rehabilitation system for recovering motor function in human hands after injury Human-like robotic eye and head movements in human–machine interactions A state-of-the-art resource for graduate students and researchers

Biomass based porous carbon for supercapacitor by hydrothermal assisted activating method

A facile route has been employed to synthesize a series of high performance activated carbons as the electrode material for supercapacitors. The structure of the carbons are characterized by N2 adsorption/desorption and FTIR spectroscopy. The electrochemical performances of the carbons as an electrode material were evaluated by cyclic voltammetry test and galvanostatic charge/discharge measurements. As a biomass derived carbon, KOH-1 exhibits high capacity, good rate capability and high energy density, indicating the promising application of hydrothermal combining with KOH activation method for biomass materials that used in supercapacitor