An improved RRT behavioral planning method for robots based on PTM algorithm.

For multi-dimensional high-order nonlinear systems with unstable path quality in parameter and extension terms, we developed a new fast search random tree strategy. First, we established a high-order Lipschitz vector field dynamic system to adapt to high-order systems of multi-degree-of-freedom robots, with the complex obstacle function being one of its key components. Secondly, we designed a classification gap filtering network layer (Classification LSTM) to screen training data models and ensure the global stability of data in path design. Additionally, the visual sensors deployed in the unit area effectively implement the path marking backtracking strategy and dead zone path simplification. Finally, three examples are provided to verify the effectiveness of this design method.

Color changing object recognition and grabbing technology based on crystal butterfly algorithm and adaptive imitation.

Implementing grasping tasks under color and multi scene promotion conditions is a key technology. This study proposes a recognition and grasping technique based on the crystal butterfly algorithm and adaptive imitation synthesis. Firstly, inspired by the movement trajectory of butterflies, a dynamic node tracking method called "Butterfly Trajectory" was designed. It can complete dynamic trajectory tracking under geometric constraints and achieve route memory. The second color dynamic recognition technology (CDR) has been proposed. It can quickly extract brightness, transparency, and color saturation obtained from multiple angles. Improve the feature extraction speed of Region CNN (R-CNN) instead of traditional methods (HOG). In addition, an adaptive imitation synthesis technique (AISP) is used to achieve the multi scenario promotion of grasping technology. Finally, simulation and physical testing were provided to verify the effectiveness of the design scheme in this article.

Online control parameter optimization design for multi-machine coordinated loading system of hazardous substances.

To address the parameter instability issues in hazardous materials handling during multi-machine loading and unloading operations, we propose a Full-Scale Smart Parameter Optimization Control (FSPOC) system specifically designed for multi-machine coordination. This system leverages a novel fish scale prediction algorithm tailored for cooperative multi-machine environments. Initially, the fish scale prediction algorithm, inspired by bionic fish scales, is developed to predict future system behavior by analyzing historical data. Building on this algorithm, we introduce a disturbance cancellation control theorem and design a parameter optimization controller to enhance stability in high-dimensional nonlinear spaces. The FSPOC method is then applied to a multi-machine cooperative system, enabling online distributed parameter optimization for complex systems with multiple degrees of freedom. The effectiveness of the proposed method was validated through simulations, where it was compared with two other optimization techniques: Genetic Algorithm-based PID (GAPID) and Chaotic Atomic Search Algorithm-based PID (CHASO). The simulation results confirm the superiority of the FSPOC method.

Hemodynamic Solution Computation and Pathological Analysis in the Circle of Willis.

Hemodynamic indexes will change significantly compared to the normal range of many vascular diseases, therefore it is necessary to establish hemodynamic computation model. Blood circulation is periodically forced huge fluid flow network, the heart is generator of the entire fluid network, based on this hemodynamic characteristics, the circle of Willis's structure is simplified from the perspective of network and hemodynamics. According to hemodynamic equations and circuit graph theory, models blood flow network of the periodically forced hemodynamic equation, obtains the approximate solution of the harmonic waves form based on averaging computation. We apply this model in the network of the circle of Willis, which may help explain the development processes of cerebral circulation disease. The simulation results show that computing results consistent with the clinical observation of blood flow changes in cerebral infarction.

Control modeling and Chinese acupuncture treatment on cerebral circulation.

Cerebral hemodynamic parameters are related to the occurrence and development of the cerebral vascular diseases. This paper proposes a new possible method for control treatment on cerebral circulation network diseases. Cerebral circulation is taken as a kind of fluid network that should be controlled. The acupuncture treatment in traditional Chinese medicine is used as an actuator, whose design principle is changing the artery pressure and resistance of the cerebral circulation to increase the blood flow, so as to achieve the purpose of treating cerebral circulation diseases. Clinical data of acupuncture and moxibustion treatment has also preliminarily proved the correctness of this method.

Hemodynamic assessment and computation on vertebral artery stenosis.

Cerebral vascular diseases are associated with cerebral hemodynamic parameter, which is difficult to observe and examine. This paper has proposed a new modeling method based on network and hemodynamics. The harmonic solution to the 18 branches of the circle of Willis is acquired through the plane network. We use this method to explain the development processes of vertebral artery diseases, and the hemodynamic assessment of vertebral artery stenosis have been done to prove this method.