Guochen Niu

Research on robotic arm path planning based on an improved bidirectional RRT* algorithm

Guochen Niu, Biao Tang, Xue Wang

Abstract To enable efficient, smooth, and obstacle-free path planning for robotic arms during cleaning operations, this study introduces an enhanced bidirectional RRT* algorithm grounded in arm kinematics. Addressing limitations like poor goal orientation and winding trajectories, the method integrates strategies such as …

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Testing of magnetic properties of amorphous and nanocrystalline alloys applied out-of-plane stress at wide frequency range

Changgeng Zhang, Guochen Niu, Wenbin Meng, Yongjian Li

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Research on Autonomous Driving Decision-making Method Based on Inverse Reinforcement Imitation Learning

Zhiheng Han, Guochen Niu

In response to the challenges of low sample efficiency and unstable training in automatic driving behavioral decision-making models, we propose a novel approach that combines behavioral cloning with generative adversarial imitation learning. By incorporating a time-weighting function into the loss function, we …

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An Off-Axle Full-Trailer Vehicle Control Method Based on Adaptive LQR

Guochen Niu, Hui Xia, Dandan Hu

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Improved YOLOv8s Algorithm for Object Detection in Airfield Area

Guochen Niu, Hongcheng Zhou

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Multiscale feature enhancement algorithm for target detection in traffic scenarios

Guochen Niu, Linquan Tan

To address and resolve the issue of visual detection errors due to the different scale of the target and more blockage in complex traffic environments, a multi-scale enhanced traffic scenario target detection algorithm based on YOLOv5 has been proposed. A multi-branch stacking …

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Improved PointPillars target detection algorithm based on traffic target

Guochen Niu

There exist two primary challenges within point cloud-based PointPillars targets detecting algorithm: the inefficiency in detecting small objects and the limited capacity of the PointPillars backbone network to extract features comprehensively. These hinders achieving the exacting standards of accuracy and instantaneous performance …

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Fast Ground Segmentation Method Based on Lidar Point Cloud

Guochen Niu, Yibo Tian, Xiangyu Sun, Zhiheng Han

Abstract A ground segmentation method based on line fitting of adjacent points was proposed for accurate and real-time segmentation of non-ground information from the LiDAR point cloud. Firstly, the point cloud is divided into several ordered regions depending upon the distribution characteristics …

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Point cloud map construction method based on ground constraint and loop detection

Guochen Niu, Yu Xiong, Yibo Tian

High-precision point cloud map is critical for Level 3 and above autonomous vehicles to operate effectively. When autonomous vehicles only use LiDAR to construct the point cloud map, drift deviation will occur in the horizontal and vertical directions, which affects the quality …

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A fast grey wolf optimization algorithm with exponential iterative search

Qijun Luo, Yanqi Yu, Guochen Niu

Aiming at the problems of traditional Grey Wolf Optimization algorithm (GWO), such as easy to fall into local optimization, low precision of optimization, and slow convergence speed, a fast grey wolf optimization algorithm with exponential iterative search is proposed. The tent chaotic …

Unmanned vehicle positioning and mapping method based on multi-constraint factor graph optimization

Guochen Niu, Yu Wang

Path Planning of Continuum Robot Based on Path Fitting

Guochen Niu, Yunxiao Zhang, Wenshuai Li

The Continuum Robot has a multiredundant dof structure, which is extremely advantageous in the unstructured environment, and can complete such tasks as aircraft fuel tank inspection. However, due to its complex kinematics and coupling of joint motion, its motion path planning is …

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