Search

Trajectory planning technology is one of the key technologies in the field of autonomous driving. However, the current planning algorithms cannot meet the optimal trajectory requirements to a certain extent. A novel algorithm is proposed to optimize the A*-artificial potential field (APF) method for generating optimal trajectories. To address the issue of path nonoptimality, improvements are made to the node expansion in the traditional A* algorithm. In addition, the traditional four-connected search strategy is enhanced with a new hybrid search strategy. Nodes are pruned to reduce path length. To handle multiturns in the A* algorithm, the trajectory is smoothed using a third-order Bezier curve, ensuring that the curvature of the trajectory is continuous. To address the issue of invalid repulsive force existing in the APF, the virtual ellipse theory is proposed. This theory aims to eliminate the impact of invalid repulsive force within certain ranges. At the same time, constraints such as road boundary repulsive force and virtual lane line gravitational force are incorporated to ensure safe vehicle travel. Finally, the optimized A*-APF algorithm is proposed to introduce an artificial potential energy term in the heuristic function of the A* algorithm to optimize trajectory generation. The algorithm is also verified in three scenarios on a real vehicle: vehicle and pedestrian avoidance (Vp) experiment, parallel obstacle avoidance (Po) experiment, and staggered stopping (Ss) experiment. The effectiveness of the algorithm is verified through the analysis of four parameters, namely, trajectory, speed, heading angle, and steering wheel angle.

This paper presents a method for the length-pressure hysteresis modeling of pneumatic artificial muscles (PAMs) by using a modified generalized Prandtl-Ishlinskii (GPI) model. Different from the approaches for establishing the GPI models by replacing the linear envelope functions of operators with hyperbolic tangent and exponential envelop functions, the proposed model is derived by modifying the envelope functions of operators into arc tangent functions, which shows an improvement in the modeling accuracy. The effectiveness of the proposed model is verified by the experimental data of a PAM. Furthermore, its capacity in capturing the hysteresis relationship between length and pressure is testified by giving different input pressure signals. With regard to the computational efficiency, the influence of the number of operators on the modeling accuracy is discussed. Furthermore, the inversion of the GPI model is derived. Its capability of compensating the hysteresis nonlinearities is confirmed via the simulation and experimental study.

Introduction: The current digital twin systems usually have the drawback of high cost and complex technology, and it is necessary to develop a simple solution to reduce the cost and cycle for the development of digital twin systems, especially for small projects or systems with simple structures. Objective: A low-cost patent technology of digital twin system was proposed by taking the motion control and state monitoring system (MCSMS) of pneumatic muscle as an example. Methods: The MCSMS is developed based on the browser/server architecture. The software of 3ds Max and SolidWorks are used to make the virtual model, Three.js and JavaScript are applied to build the browser side. Data of the physical world is collected and processed on the server side firstly, and then is sent to the browser side through HTTP communication protocol to realize data interchange between the browser and server. Results: In the roaming experiment and the experiment of motion control and state monitoring of pneumatic muscle, the MCSMS can work smoothly without obvious delay and has good real-time performance, which can realize the 3D visual monitoring of the pneumatic muscle very well. Conclusion: The experimental results indicate that the proposed method possesses the ability of good feasibility and effectiveness.