 |
Second Prize in 18th National College Student Smart Car Competition2023/08
In the 18th National College Student Smart Car Competition Electric Relay Group, I was primarily responsible for software design for the charging section and communication and coordination between two cars.
I had to ensure not only the efficiency and stability of the charging process but also the precise data exchange and collaborative operation between the two vehicles. By writing and optimizing the charging algorithm, I ensured the efficient transfer of energy.
At the same time, I designed a communication protocol that allowed the two cars to share critical information such as position, speed, and charging status in real-time, achieving seamless relay charging.
Additionally, I was responsible for debugging and optimizing potential issues that might arise during the coordination process of the two cars, ensuring the smoothness and reliability of the entire charging process.
|
 |
第18届全国大学生智能汽车竞赛二等奖2023/08
在第十八届全国大学生智能车竞赛电能接力组的比赛中,我主要负责充电部分的软件设计以及双车之间的通信与联调工作。
我不仅要确保充电过程的高效和稳定,还要实现两辆车之间精确的数据交换和协同作业。通过编写和优化充电算法,我确保了能量的高效传输。
同时,我还设计了一套通信协议,使得两辆车能够实时共享位置、速度和充电状态等关键信息,实现无缝接力充电。
此外,我还负责调试和优化双车联调过程中可能出现的问题,确保整个充电过程的流畅性和可靠性。
|
 |
Second Prize in 17th National College Student Smart Car Competition2022/08
I participated in the 17th National College Student Smart Car Competition in the iFlytek Smart Service Group, and independently completed the entire process from data collection, annotation to model training.
I also learned about neural network quantization and deployment techniques, and successfully deployed YoloV5 for object detection on the Jetson Nano platform.
At the same time, I gained a preliminary understanding of the communication methods in the ROS system, which is crucial for the coordination and integration of different modules within the team.
|
 |
第17届全国大学生智能汽车竞赛二等奖2022/08
本人参与第17届全国大学生智能汽车竞赛讯飞智慧服务组,独立完成了从数据采集、标注到模型训练的全过程。
我还学习了神经网络的量化和部署技术,在Jeston Nano上部署了YoloV5用于目标检测。
同时,我也初步了解了ROS系统的通信方法,这对于团队中不同模块间的协调和整合起到了关键作用。
|
 |
Second Prize in 17th National College Student Smart Car Competition2022/08
I served as the team captain in the 17th National College Student Smart Car Competition, Balance Beacon Group, leading our team to secure the second prize in the category.
Within the team, I was primarily responsible for the task of beacon light detection using a camera.
I improved the beacon light detection algorithm that I developed last year to adapt to the car that could rock back and forth.
Video
|
 |
第17届全国大学生智能汽车竞赛二等奖2022/08
我在第17届全国大学生智能汽车竞赛平衡信标组中担任队长并带领团队收获全国二等奖。
在团队中我主要承担摄像头识别信标灯的工作,改进了在上一届中开发的信标灯识别算法,使其能够适应前后摇晃的车模。
视频
|
 |
Second Prize in 16th National College Student Smart Car Competition 2021/08
I served as the team captain in the 16th National College Student Smart Car Competition, Energy-saving Beacon Group, leading our team to secure the second prize in the category.
Within the team, I was primarily responsible for the task of beacon light detection using a camera.
The main challenge of this task was to achieve real-time detection of small beacon lights at a distance on an embedded platform with limited computational capabilities, while mitigating interference caused by reflections and ambient lighting.
I began by employing digital image processing techniques to filter, binarize, and detect edges in the images.
Following this, I calculated the connected components within the images and extracted features such as size, coordinates, and rectangularity of these components.
Subsequently, I fed these features into a multi-layer perceptron model to perform binary classification on each connected component.
During the implementation, I manually derived the network and summarized patterns, developing a compact framework capable of stacking multiple fully connected layers for parameter tuning using C program language, which ultimately led to significant results.
Video1
Video2
|
 |
第16届全国大学生智能汽车竞赛二等奖 2021/08
我在第16届全国大学生智能汽车竞赛节能信标组中担任队长并带领团队收获全国二等奖。
在团队中我主要承担摄像头识别信标灯的工作。
该工作的难点主要在于如何在计算能力受限的嵌入式平台中实现对较远的小型信标灯的实时检测并去除由于反光和环境灯光造成的干扰。
我首先利用数字图像处理技术对于图像进行滤波、二值化与边缘检测,随后计算图像的各个联通域,并提取连通域的大小、坐标、矩形度等特征。
随后,我将这些特征输入到一个多层感知机模型中,对每个连通域进行二分类识别。
在实现这一过程中,我通过手动对网络进行求导并总结规律,使用C语言开发了一个可以堆叠多个全连接层的小型框架,用于参数调整,最终取得了显著的成效。
视频1
视频2
|
 |
Gold Medal in the CCF CCSP 20222022/12
|
 |
2022CCF大学生计算机系统与程序设计竞赛金奖2022/12
|
 |
Gold Medal in the CCF CCSP (East China) 20222022/12
|
 |
2022CCF大学生计算机系统与程序设计竞赛(华东赛区)金奖2022/12
|
 |
Gold Medal in the CCF CCSP (East China) 20212021/12
|
 |
2021CCF大学生计算机系统与程序设计竞赛(华东赛区)金奖2021/12
|
CSP2019 |
Second Prize in the Advanced Group of the CSP2019 competition.2019/11 |
CSP2019 |
CSP2019提高组二等奖2019/11 |
NOIP2018 |
Second Prize in the Advanced Group of the NOIP2018 competition.2018/11 |
NOIP2018 |
NOIP2018提高组二等奖2018/11 |
NOIP2016 |
First Prize in the Popularization Group of the NOIP2016 competition.2016/11 |
NOIP2016 |
NOIP2016普及组一等奖2016/11 |