Hand gesture recognition in complex background based on convolutional pose machine and fuzzy gaussian mixture models

© 2020, The Author(s). Hand gesture is one of the most intuitive and natural ways for human to communicate with computers, and it has been widely adopted in many human–computer interaction applications. However, it is still a challenging problem when confronted with complex background, illumination variation and occlusion in real-world scenarios. In this paper, a two-stage hand gesture recognition method is proposed to tackle these problems. At the first stage, hand pose estimation is developed to locate the hand keypoints using the convolutional pose machine, which can effectively localize hand keypoints even in a complex background. At the second stage, the Fuzzy Gaussian mixture models (FGMMs) are tailored to reject the nongesture patterns and classify the gestures based on the estimated hand keypoints. Extensive experiments are conducted to evaluate the performance of the proposed method, and the result demonstrates that the proposed algorithm is effective, robust, and satisfactory in real-time scenarios

Enhancing Heat Transfer in Internal Combustion Engine by Applying Nanofluids

Nanofluids exhibit novel properties including significant heat transfer properties that make them potentially useful in internal combustion engine cooling. However, although there is a substantial number of mechanisms proposed, modeling works related to their enhanced thermal conductivity, systematic mechanisms, or models that are suitable for nanofluids are still lacked. With molecular dynamics simulations, thermal conductivities of nanofluids with various nanoparticles have been calculated. Influence rule of various factors for thermal conductivity of nanofluids has been studied. Through defining the ratio of thermal conductivity enhancement by nanoparticle volume fraction, Κ, the impacts of nanoparticle properties for thermal conductivity are further evaluated. Furthermore, the ratio of energetic atoms in nanoparticles, E, is proposed to be an effective criterion for judging the impact of nanoparticles for the thermal conductivity of nanofluids. Mechanisms of heat conduction enhancement are investigated by MD simulations. Altered microstructure and movements of nanoparticles in the base fluid are proposed to be the main reasons for thermal conductivity enhancement in nanofluids. Both the static and dynamic mechanisms for heat conduction enhancement in nanofluids have been considered to establish a prediction model for thermal conductivity. The prediction results of the present model are in good agreement with experimental results

Head-raising of snake robots based on a predefined spiral curve method

© 2018 by the authors. A snake robot has to raise its head to acquire a wide visual space for planning complex tasks such as inspecting unknown environments, tracking a flying object and acting as a manipulator with its raising part. However, only a few researchers currently focus on analyzing the head-raising motion of snake robots. Thus, a predefined spiral curve method is proposed for the head-raising motion of such robots. First, the expression of the predefined spiral curve is designed. Second, with the curve and a line segments model of a snake robot, a shape-fitting algorithm is developed for constraining the robot's macro shape. Third, the coordinate system of the line segments model of the robot is established. Then, phase-shifting and angle-solving algorithms are developed to obtain the angle sequences of roll, pitch, and yaw during the head-raising motion. Finally, the head-raising motion is simulated using the angle sequences to validate the feasibility of this method

Disturbance observer enhanced variable gain controller for robot teleoperation with motion capture using wearable armbands

Disturbance observer (DOB) based controller performs well in estimating and compensating for perturbation when the external or internal unknown disturbance is slowly time varying. However, to some extent, robot manipulators usually work in complex environment with high-frequency disturbance. Thereby, to enhance tracking performance in a teleoperation system, only traditional DOB technique is insufficient. In this paper, for the purpose of constructing a feasible teleoperation scheme, we develop a novel controller that contains a variable gain scheme to deal with fast-time varying perturbation, whose gain is adjusted linearly according to human surface electromyographic signals collected from Myo wearable armband. In addition, for tracking the motion of operator’s arm, we derive five-joint-angle data of a moving human arm through two groups of quaternions generated from the armbands. Besides, the radial basis function neural networks and the disturbance observer-based control (DOBC) approaches are fused together into the proposed controller to compensate the unknown dynamics uncertainties of the slave robot as well as environmental perturbation. Experiments and simulations are conducted to demonstrated the effectiveness of the proposed strategy

A Public Information Precoding for MIMO Visible Light Communication System Based on Manifold Optimization

Visible light communication (VLC) is an attractive subset of optical communication that provides a high data rate in the access layer of the network. The combination of multiple inputmultiple output (MIMO) with a VLC system leads to a higher speed of data transmission named as MIMO-VLC system. In multi-user (MU) MIMO-VLC, a LED array transmits signals for users. These signals are categorized as signals of private information for each user and signals of public information for all users. The main idea of this paper is to design an omnidirectional precoding to transmit the signals of public information in the MUMIMO-VLC network. To this end, we propose to maximize the achievable rate which leads to maximizing the received mean power at the possible location of the users. Besides maximizing the achievable rate, we consider equal mean transmission power constraint in all LEDs to achieve higher power efficiency of the power amplifiers used in the LED array. Based on this we formulate an optimization problem in which the constraint is in the form of a manifold and utilize a gradient method projected on the manifold to solve the problem. Simulation results indicate that the proposed omnidirectional precoding can achieve superior received mean power and bit error rate with respect to the classical form without precoding utilization.Comment: This paper has been submitted to an IEEE Journa