Recently, the concept of human-robot collaboration has raised many research interests. Instead of robots replacing human workers in workplaces, human-robot collaboration allows human workers and ...robots working together in a shared manufacturing environment. Human-robot collaboration can release human workers from heavy tasks with assistive robots if effective communication channels between humans and robots are established. Although the communication channels between human workers and robots are still limited, gesture recognition has been effectively applied as the interface between humans and computers for long time. Covering some of the most important technologies and algorithms of gesture recognition, this paper is intended to provide an overview of the gesture recognition research and explore the possibility to apply gesture recognition in human-robot collaborative manufacturing. In this paper, an overall model of gesture recognition for human-robot collaboration is also proposed. There are four essential technical components in the model of gesture recognition for human-robot collaboration: sensor technologies, gesture identification, gesture tracking and gesture classification. Reviewed approaches are classified according to the four essential technical components. Statistical analysis is also presented after technical analysis. Towards the end of this paper, future research trends are outlined.
•The authors introduced a remote HRC system inspired by the concept of CPS.•The authors designed a remote robot control system and an AR feedback system.•The system can flexibly work in four ...different modes.•The system is implemented and tested in different scenarios.
Collaborative robot's lead-through is a key feature towards human–robot collaborative manufacturing. The lead-through feature can release human operators from debugging complex robot control codes. In a hazard manufacturing environment, human operators are not allowed to enter, but the lead-through feature is still desired in many circumstances. To target the problem, the authors introduce a remote human–robot collaboration system that follows the concept of cyber–physical systems. The introduced system can flexibly work in four different modes according to different scenarios. With the utilisation of a collaborative robot and an industrial robot, a remote robot control system and a model-driven display system is designed. The designed system is also implemented and tested in different scenarios. The final analysis indicates a great potential to adopt the developed system in hazard manufacturing environment.
With the emergence of a series of global security incidents, scholars and observers have placed increasing importance on nontraditional security (NTS). Since 2012, Xi Jinping’s regime has emphasized ...NTS issues and cooperation, which begs the question “What is the role of NTS in China’s foreign policy, and how is it shaped?” This study analyzes articles that include the term “nontraditional security” (“非传统安全”) in
The People’s Daily
newspaper since its first mention in 2001. Focusing particularly on the period between 2012 and 2019, the study explains China’s securitization process and its motivations toward NTS issues. By analyzing case studies of the NTS issues of terrorism, environmental issues, and cybersecurity, and further summarizing the logic in common behind the Chinese government’s process of securitizing NTS issues, this paper highlights the correlation between the characteristics of China’s NTS and China’s major foreign policy initiatives that play an active role in leading international efforts to enhance global governance and exploring new models of cooperation. Based on an analysis of China’s emphasis on promotion of NTS and provision of public goods, I argue that NTS has played an increasingly important role in China’s pursuit of greater influence in global governance mechanisms.
Timely context awareness is key to improving operation efficiency and safety in human-robot collaboration (HRC) for intelligent manufacturing. Visual observation of human workers’ motion provides ...informative clues about the specific tasks to be performed, thus can be explored for establishing accurate and reliable context awareness. Towards this goal, this paper investigates deep learning as a data driven technique for continuous human motion analysis and future HRC needs prediction, leading to improved robot planning and control in accomplishing a shared task. A case study in engine assembly is carried out to validate the feasibility of the proposed method.
A deep neural network (DNN)-based new pansharpening method for the remote sensing image fusion problem is proposed in this letter. Research on representation learning suggests that the DNN can ...effectively model complex relationships between variables via the composition of several levels of nonlinearity. Inspired by this observation, a modified sparse denoising autoencoder (MSDA) algorithm is proposed to train the relationship between high-resolution (HR) and low-resolution (LR) image patches, which can be represented by the DNN. The HR/LR image patches only sample from the HR/LR panchromatic (PAN) images at hand, respectively, without requiring other training images. By connecting a series of MSDAs, we obtain a stacked MSDA (S-MSDA), which can effectively pretrain the DNN. Moreover, in order to better train the DNN, the entire DNN is again trained by a back-propagation algorithm after pretraining. Finally, assuming that the relationship between HR/LR multispectral (MS) image patches is the same as that between HR/LR PAN image patches, the HR MS image will be reconstructed from the observed LR MS image using the trained DNN. Comparative experimental results with several quality assessment indexes show that the proposed method outperforms other pan-sharpening methods in terms of visual perception and numerical measures.
In this paper, we propose a variational Bayesian method for Retinex to simulate and interpret how the human visual system perceives color. To construct a hierarchical Bayesian model, we use the Gibbs ...distributions as prior distributions for the reflectance and the illumination, and the gamma distributions for the model parameters. By assuming that the reflection function is piecewise continuous and illumination function is spatially smooth, we define the energy functions in the Gibbs distributions as a total variation function and a smooth function for the reflectance and the illumination, respectively. We then apply the variational Bayes approximation to obtain the approximation of the posterior distribution of unknowns so that the unknown images and hyperparameters are estimated simultaneously. Experimental results demonstrate the efficiency of the proposed method for providing competitive performance without additional information about the unknown parameters, and when prior information is added the proposed method outperforms the non-Bayesian-based Retinex methods we compared.
Quadruped robots, with their superior terrain adaptability and flexible movement capabilities, demonstrate greater application potential in complex environments compared to traditional ground robots. ...However, their non-negligible body shape and anisotropic motion characteristics complicate the achievement of high-precision motion planning and autonomous navigation. In this paper, we propose a safe and robust motion planning system tailored for autonomous navigation of quadruped robots in cluttered environments. We adopt a hierarchical architecture and decompose the planning process into front-end searching and back-end optimization. In the front-end searching stage, the robot finds a smooth, feasible, and energy-efficient initial trajectory with safety consideration. In the back-end optimization stage, we leverage B-splines to enhance the trajectory smoothness, safety, and motion stability. Finally, the time allocation is fine-tuned through iterative refinement, ensuring the feasibility of the optimized trajectory. Our method is extensively validated in challenging simulations as well as in real-world testing environments, benchmark comparisons also demonstrate the improved performance of our method.
Intuitive and robust multimodal robot control is the key toward human-robot collaboration (HRC) for manufacturing systems. Multimodal robot control methods were introduced in previous studies. The ...methods allow human operators to control robot intuitively without programming brand-specific code. However, most of the multimodal robot control methods are unreliable because the feature representations are not shared across multiple modalities. To target this problem, a deep learning-based multimodal fusion architecture is proposed in this paper for robust multimodal HRC manufacturing systems. The proposed architecture consists of three modalities: speech command, hand motion, and body motion. Three unimodal models are first trained to extract features, which are further fused for representation sharing. Experiments show that the proposed multimodal fusion model outperforms the three unimodal models. This paper indicates a great potential to apply the proposed multimodal fusion architecture to robust HRC manufacturing systems.
The molecular mechanisms of circular RNAs (circRNAs) in extracellular vesicles (EVs) associated with glioma radioresistance remain unknown. The aim of the present study was to assess the differential ...circRNA expression profiles between EVs isolated from U251 cells and EVs isolated from radioresistant U251 (RR‑U251) cells. Identified circRNAs in EVs isolated from RR‑U251 cells (RR‑EVs) act as a U251 microRNA (miRNA) sponge. The circRNA expression was determined using RNA sequencing (RNA‑seq) technique. A total of 1,235 circRNAs were detected. We identified 63 upregulated and 48 downregulated circRNAs in RR‑EVs compared with those from U251 cells (Nor‑EVs). The expression level of candidate circATP8B4 was confirmed using real‑time quantitative PCR. It was significantly higher in RR‑EVs than in Nor‑EVs. Expression profile of RR‑U251 and U251 miRNAs was conducted. miRanda and RNAhybrid softwares was used to predict the U251 downregulated miRNAs interacting with circATP8B4. CircATP8B4 from RR‑EVs may be transferred to normal glioma U251 cells and act as an miR‑766 sponge to promote cell radioresistance. In conclusion, using RNA‑seq and bioinformatics, it was found that circATP8B4 in RR‑EVs acts as a U251 miR‑766 sponge, which may be involved in glioma radioresistance.
This work presents a synthesis process and flocculation characteristics of an eco-friendly flocculant based on bamboo pulp cellulose (BPC) from Phyllostachys heterocycla. Ployacrylamide (PAM) was ...grafted onto the BPC by free-radical graft copolymerization in homogeneous aqueous solution. The optimal synthesis conditions of the bamboo pulp cellulose-graft-ployacrylamide flocculant (BPC-g-PAM) and its performance on wastewater treatments were investigated. A UV-based method was used to rapidly determine the degree of substitution (DS) of BPC. The results showed that, under the optimal synthesis conditions, the obtained BPC-g-PAM held a grafting ratio of 43.8% and DS of 1.31. Turbidity removal of the product reached 98.0% accompanying with the significant flocculation and sedimentation in target suspensions. The flocculation mechanism was explored by means of zeta potential method. For negatively charged contaminants, like kaolin clay particles, the BPC-g-PAM could remove the contaminants efficiently via bridging and charge neutralization in acidic or neutral environment.
Proposed synthesis process and potential flocculation mechanism of the BPC-g-PAM product. Display omitted
•A BPC-g-PAM flocculant is prepared based on the cellulose from Phyllostachys heterocycla.•The flocculation effect and mechanism of the novel BPC-g-PAM are investigated.•The resultant BPC-g-PAM flocculant is biodegradable and environment-friendly.•The BPC-g-PAM flocculant has excellent turbidity-removal capacity.•An effluent from paper mill was used to evaluate the flocculation of BPC-g-PAM.
PDF
