In order to address the issue of optimal pathfinding in autonomous mobile robot navigation, an improved path planning scheme based on the traditional A* algorithm is proposed. Firstly, aiming at the problem of collision and low planning search efficiency in traditional A* algorithm, a safety distance is set, and the Euclidean distance calculation method is selected in the heuristic function, constructing a cost function with dynamically adjustable heuristic function weights. Secondly, to smooth out the non-smooth paths generated by traditional A* algorithm, a Bezier curve smoothing algorithm is employed for path smoothing. Then, through simulation experiments, the significant improvements of the algorithm in terms of planning efficiency, safety, and path smoothness are verified. Finally, through autonomous navigation experiments, the feasibility of the improved A* algorithm is demonstrated. The research demonstrates that the algorithm designed in this paper can plan the optimal path and safely and efficiently reach the target point.
Analyze the encryption and decryption principle of KeeLoq and the shortcomings in security, propose an improvement scheme for KeeLoq algorithm to further improve its security; and conduct experimental verification by a BCM controller of a car, the experimental method is to combine the 027 service in the UDS protocol in KeeLoq algorithm to generate key authentication between the key side and the car side, the protocol generated temporary The key is passed with the factory key and serial number to derive a new password, and finally the key generation algorithm and the communication parties obtain the improved KeeLoq key in the learning process. The performance comparison with the original KeeLoq and triple KeeLoq algorithms concludes that while improving the security of the original algorithm, it reduces the complexity of the algorithm and increases the computation rate compared to triple KeeLoq. It is more suitable for PEPS system.
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