Generating a collision-free and dynamically feasible trajectory with a better clearance in a cluttered environment is still a challenge. We propose two dynamically feasible B-spline based rapidly ...exploring random tree (RRT) approaches, which are named DB-RRT and FMDB-RRT, to achieve path planning and trajectory planning simultaneously for omnidirectional mobile robots. DB-RRT combines the convex hull property of the B-spline and RRT’s rapid expansion capability to generate a safe and dynamically feasible trajectory. Firstly, we analyze the tree’s sustainable growth ability and put forward the dynamically feasible region. A geometric method is proposed to judge whether finding a dynamically feasible trajectory quickly. Secondly, we design two steer functions to guide the tree’s growth, improve efficiency, and decrease the number of iterations. To further increase the clearance and reduce the randomness of the trajectory, we propose FMDB-RRT, which uses the path of fast marching to guide the rapid growth of DB-RRT. Then, assuming that the number of sampled points is sufficient to represent the dynamically feasible region, the DB-RRT is proved to be probabilistically complete. Finally, by conducting experimental comparisons with other algorithms in different environments and deploying the proposed algorithm to an omnidirectional mobile robot, the effectiveness and good performance of the algorithm have been verified.
Nowadays, computer numerical control (CNC) machine tool undertakes more processing tasks than other common machine tools because of its highly automated machining ability and high performance. ...However, due to the lack of intelligence in machining process planning, machining procedure of products mostly depends on process planners rather than CNC machine tools. To make product quality less dependable on process planner’s ability and improve the efficiency of process planning in order to fulfill changeable market, this paper presents an approach to design and develop CNC machining process knowledge base using cloud technology. The general standard STEP-NC is mapped to web ontology language (OWL) to describe machining process-related knowledge in a readable and comprehensible way. This mapping relation also makes knowledge suitable for storage in HBase. Through this ontology model, descriptive and logical knowledge can be collected. Hadoop platform is used in this approach to provide the NoSQL database HBase for large-scale knowledge storage and MapReduce programming model for large-scale knowledge processing. Taking advantage of MapReduce, knowledge query engine and reasoning engine can be developed. Users can submit task and resource descriptive files to the cloud through CNC controller and get machining process solutions from knowledge base. Evaluation mechanism is also adopted to filter low-quality knoweldge.
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Non-uniform rational B-spline (NURBS) curve has been widely used in manufacturing systems. A good interpolator can help the system to improve the contour accuracy and get smooth dynamics performance, ...but it is hard to get a balance between the interpolation performance and computational load. As the derivative and curvature of NURBS curves used in manufacturing systems are high-order continuous, it is possible to predict a desired interpolation arc length based on the relationship of historical feed chord length and its corresponding arc length in one interpolation cycle. Therefore, this paper proposes a novel interpolation method, which consists three stages. Firstly, a NURBS curve is split into several high-order continuous segments based on its degrees and control points. Secondly, a prediction model based on Newton’s divided differences interpolation equation is derived from the relationship of interpolated chord length and its corresponding arc length, so that the target arc length of the next interpolation cycle can be predicted. Finally, target parameter
u
of every interpolation cycle is calculated with Taylor’s expansion, whose values are corrected by iteration, and then the position of the target interpolation point can be achieved. Performance of the proposed algorithm is tested and compared with other methods, and the simulation results show the proposed method can achieve smaller velocity fluctuation with low computational load.
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The development of computer, internet and information technology puts forward higher demands for Computer Numerical Control (CNC) machine tools to improve the intelligence in many aspects. Among ...these aspects, intelligent process planning plays an important role in current changeable market and customized product promotion by shortening production cycle and providing more stable process planning ability. To realize intelligent process planning, a CNC controller with cloud knowledge base support is proposed with ability of making process planning autonomously based on workpiece design. Previous work of knowledge model and cloud knowledge base framework design is introduced, and then this paper focuses on the complete process planning method within the intelligent CNC controller. Both interactivity between knowledge base and CNC controller, and query/infer mechanism in knowledge base are illustrated in detail. A case study of two shafts process planning is shown to demonstrate the feasibility of the intelligent process planning method.
Autonomous exploration and remote sensing using robots have gained increasing attention in recent years and aims to maximize information collection regarding the external world without human ...intervention. However, incomplete frontier detection, an inability to eliminate inefficient frontiers, and incomplete evaluation limit further improvements in autonomous exploration efficiency. This article provides a systematic solution for ground mobile robot exploration with high efficiency. Firstly, an integrated frontier detection and maintenance method is proposed, which incrementally discovers potential frontiers and achieves incremental maintenance of the safe and informative frontiers by updating the distance map locally. Secondly, we propose a novel multiple paths planning method to generate multiple paths from the robot position to the unexplored frontiers. Then, we use the proposed utility function to select the optimal path and improve its smoothness using an iterative optimization strategy. Ultimately, the model predictive control (MPC) method is applied to track the smooth path. Simulation experiments on typical environments demonstrate that compared with the benchmark methods, the proposed method reduce the path length by 27.07% and the exploration time by 27.09% on average. The real-world experimental results also reveal that our proposed method can achieve complete mapping with fewer repetitive paths.
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The autonomous navigation of mobile robots in the industrial environment has received more and more attention. However, how to ensure the safe and smooth movement of robots is still an open problem. ...This paper proposes an online motion planning method that can guarantee the safe and smooth navigation of Mecanum-wheeled robots in the industrial environment. The method includes two parts: path planning and trajectory planning. In the path planning part, we propose a method called Safe-Connect RRT (SC-RRT) based on Generalized Voronoi Diagram (GVD) and RRT-Connect. SC-RRT improves the branch growth of the RRT-Connect algorithm and reduces the sampling space so that the path away from the obstacle can be quickly obtained. In the trajectory planning part, we use the S-shaped ACC/DEC algorithm to obtain the initial time allocation between path points. Then, the time interval of corresponding path points can quickly get using the dichotomy method. After that, the trajectory is fitted by the cubic spline method in combination with the path point and the allocated time. Dynamic feasibility check and time reallocation mechanism guarantee to obtain a smooth trajectory that satisfies the dynamic constraints. Finally, simulations with different kinds of environment and practical experiments with our own designed Mecanum-wheeled robot are conducted to verify the good performance and effectiveness of the proposed method.
Objective
This survey investigated the relationship between social isolation, depression, nutritional status and quality of life among community-dwelling older adults during COVID-19.
Design
This was ...a cross-sectional survey study.
Setting
Communities in Pudong New Area, Shanghai, China that have contracted with Renji Hospital, affiliated with Shanghai Jiao Tong University School of Medicine.
Participants
From May to July 2022, 406 community-dwelling older adults were selected by convenience sampling in Shanghai, China.
Primary and secondary outcome measures
The Lubben Social Network Scale, Geriatric Depression Scale, 36-item Short Form Health Survey Scale and risk assessment of malnutrition were used in older adults. Mediation models were constructed to determine the mediating role of depression and nutritional status on social isolation and quality of life among older adults.
Results
The prevalence of social isolation among older adults in the community was 44.3%. The total social isolation score in community-dwelling older adults was positively associated with the total malnutrition risk and quality of life scores, and negatively associated with depression (p<0.01). Logistic regression demonstrated that living alone, loss of families or friends during COVID-19 and depression were risk factors for social isolation among community-dwelling older adults (p<0.05). Social isolation could directly affect the quality of life (β=0.306). In addition, depression (β=0.334) and nutritional status (β=0.058) had a significant mediating effect on the relationship between social isolation and quality of life.
Conclusions
Our findings showed that the prevalence of social isolation among older adults increased during COVID-19. Depression and nutritional status played parallel mediating roles on the effect of social isolation on quality of life. Community workers and healthcare providers should develop intervention plans to improve the status of social isolation in older adults, eliminating existing and ongoing adverse effects.
Chatter is the main problem that limits the application of industrial robots in the field of machining process. It is critically important to establish an adaptive chatter detection solution for ...robot machining process and realize the online detection of chatter. However, different from machine tool chatter, the chatter in robotic machining process is more complex to be detected due to the variable stiffness characteristics and weaker stiffness of normal industrial robot, and the existing literature has less research on this problem. This paper presents a comprehensive solution for online chatter detection in robotic machining process. Firstly, in order to detect the chatter in robotic machining process and avoid mode mixing problem in variational mode decomposition (VMD) process, an adaptive variational mode decomposition (AVMD) method based on kurtosis and instantaneous frequency is proposed, which realizes the adaptive selection of the decomposition parameter. Secondly, optimal decomposition parameters are calculated by using genetic algorithm. By optimizing the discrete step length of decomposition parameter, it greatly reduces the optimization time. Last but not least, approximate entropy, energy entropy, and proposed entropy drift coefficient are extracted to distinguish chatter and stable machining state. Simulation and experimental results show that the proposed method can meet the real-time requirements of online detection and detect the occurrence of chatter effectively.
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Recently, an image encryption scheme based on a 2D hyperchaotic map is proposed. It adopts the permutation–diffusion architecture and consists of three steps, which are permutation, forward ...diffusion, and backward diffusion. In this paper, we break this cipher with both the chosen-plaintext attack (CPA) and the chosen-ciphertext attack (CCA). According to our analysis, we found the two complex diffusion processes could be simplified into two simple diffusions and a modular addition operation. Based on this, the equivalent key can be obtained with CPA and CCA. Detailed theoretical derivations and the results of experiments confirmed the feasibility of our attack methods. When the image size was 256×256, the running time of the attacks was less than 2 hours on a laptop with a 2.59 GHz Intel Core i7 and 16 GB DDR3 memory. Other sizes of images were also tested, and some rules were found. In addition, the probability of other attacks has also been discussed, and some suggestions for improvements are given. The source codes are publicly available and can be found online.
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This paper builds an infinity shaped (“∞”-shaped) laser scanning welding test platform based on a self-developed motion controller and galvanometer scanner control gateway, takes the autogenous ...bead-on-plate welding of 304SS with 3 mm thick specimens as the experimental objects, designs the experimental parameters by the Latin hypercube sampling method for obtaining different penetration depth welded joints, and presents a methodology based on the neuroevolution of augmenting topologies for predicting the penetration depth of “∞”-shaped laser scanning welding. Laser power, welding speed, scanning frequency, and scanning amplitude are set as the input parameters of the model, and welding depth (WD) as the output parameter of the model. The model can accurately reflect the nonlinear relationship between the main welding parameters and WD by validation. Moreover, the normalized root mean square error (NRMSE) of the welding depth is about 6.2%. On the whole, the proposed methodology and model can be employed for guiding the actual work in the main process parameters’ preliminary selection and lay the foundation for the study of penetration morphology control of “∞”-shaped laser scanning welding.
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