Peng Xu

Title: Peng Xu: Innovator in Robotics and Terrain Modeling

Introduction

Peng Xu is a prominent inventor based in Haerbin, China. He has made significant contributions to the fields of robotics and terrain modeling. With a total of 2 patents, his work focuses on enhancing robotic capabilities and improving terrain analysis.

Latest Patents

One of Peng Xu's latest patents is a "Robot state planning method based on Monte Carlo tree search algorithm." This innovative method involves obtaining an initial state and a target state of a robot. By using the initial state as a starting node, the Monte Carlo tree search algorithm expands a tree until a target node reaches the desired state. This approach generates a state sequence for the robot, improving its passing capability in complex terrains by avoiding front-back coupling effects.

Another notable patent is the "Terrain modeling method that fuses geometric characteristics and mechanical characteristics." This method includes obtaining color and depth images of a detected region. It performs semantic segmentation on the color images and fuses the ground semantic information with depth information to generate point clouds. The point clouds are then mapped to a raster map, updating elevation values and generating a comprehensive terrain model that incorporates both geometric and mechanical characteristics.

Career Highlights

Peng Xu is affiliated with the Harbin Institute of Technology, where he continues to advance research in robotics and terrain modeling. His innovative approaches have garnered attention in the academic and industrial sectors.

Collaborations

He has collaborated with notable coworkers, including Liang Ding and Zongquan Deng, contributing to various research projects and patent developments.

Conclusion

Peng Xu's contributions to robotics and terrain modeling demonstrate his commitment to innovation and excellence in engineering. His patents reflect a deep understanding of complex systems and a drive to enhance technological capabilities.