Basic Information

Shitao Chen, 陈仕韬 Ph.D.

Assistant Professor 助理教授

  Institute of Artificial Intelligence and Robotics

   College of Artificial Intelligence  人工智能学院

    Xi'an Jiaotong University

Email:chenshitao@xjtu.edu.cn

 

-舜宇光学人工智能研究院

常务副院长

-华航唯实人工智能实验室

副主任

-大唐移动协同智能实验

执行主任

Research Fields

无人驾驶

Contact Information

人工智能与机器人研究所

西安市咸宁西路28 号，710049

办公室：科学馆313，创新港4号巨构

E-mail：chenshitao@xjtu.edu.cn

电话：029-82665360

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News

Honours

个人荣誉：

  • 获中国科协“青年人才托举计划”支持
  • 陕西省高校“优秀共产党员”
  • 获”ACM SIGAI China 优秀博士论文“奖
  • 获”优秀博士论文“奖
  • 获评第三届“最美三秦青年科技未来之星”
  • 入选西安交通交通青年优秀人才支持计划
  • 获博士生“国家奖学金”
  • 获研究生“国家奖学金”

学术奖励：

  • 2021  IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS Outstanding Paper Award（杰出论文奖）
  • 2021 第六届中国科协优秀科技论文提名
  • 2021 Frontiers of Information Technology & Electronic Engineering (FITEE) Best Paper Award 最佳论文
  • 2019 IEEE Intelligent Transportation Systems Conference Best Student Paper Award（最佳学生论文）
  • 2018 IEEE Intelligent Vehicles Symposium Best Student Paper Award（最佳学生论文）
  • 2017 领跑者5000——中国精品科技期刊顶尖学术论文

团队荣誉：

  • 2022 中国(淄博)智能网联汽车挑战赛
  • 第12届“中国智能车未来车挑战赛”（国家自然科学基金委员会主办），获冠军（总分第一名）
  • 第12届“中国智能车未来挑战赛”（国家自然科学基金委员会主办），安全驾驶表现、无卫星导航表现、自主泊车表现、地下车库表现等单项第一名
  • 第11届“中国智能车未来挑战赛”（国家自然科学基金委员会主办），获冠军（总分第一名）
  • 第11届“中国智能车未来挑战赛”（国家自然科学基金委员会主办），高架道路比赛、城乡道路比赛、无卫星导航乡村道路比赛、地下车库自主泊车等单项第一名
  • 第10届“中国智能车未来挑战赛”（国家自然科学基金委员会主办），获冠军（总分第一名）
  • 第10届“中国智能车未来挑战赛”（国家自然科学基金委员会主办），高架道路比赛、施工路段自主通过技术、自主泊车技术等单项第一名
  • 第9届“中国智能车未来挑战赛”（国家自然科学基金委员会主办），获冠军（总分第一名）
  • DJI全球无人机开发者大赛（联合国开发署举办），获全球第4名

Publications

[18] C. Xia, Y. Shen , Y. Yang, X. Deng, S. Chen , Member, IEEE, J. Xin , S. Member, IEEE, and N. Zheng, “Onboard Sensors-Based Self-Localization for Autonomous Vehicle With Hierarchical Map,” IEEE Trans Cybern, 2022.

[17] J. Dong, Y. Huang, S. Zhang, S. Chen, and N. Zheng, “Construct Effective Geometry Aware Feature Pyramid Network for Multi-Scale Object Detection,” 2022.

[16] A. Li, S. Chen, L. Sun, N. Zheng, M. Tomizuka, and W. Zhan, “SceGene: Bio-Inspired Traffic Scenario Generation for Autonomous Driving Testing,” IEEE Transactions on Intelligent Transportation Systems, 2021.

[15] S. Zhang, Z. Jian, X. Deng, S. Chen, Z. Nan, and N. Zheng, “Hierarchical Motion Planning for Autonomous Driving in Large-Scale Complex Scenarios,” IEEE Transactions on Intelligent Transportation Systems, 2021.

[14] J. Jiang, Z. Nan, H. Chen, S. Chen, and N. Zheng, “Predicting short-term next-active-object through visual attention and hand position,” Neurocomputing, vol. 433, pp. 212–222, 2021.

[13] S. Xie, S. Chen, J. Zheng, M. Tomizuka, N. Zheng, and J. Wang, “From human driving to automated driving: What do we know about drivers?,” IEEE Transactions on Intelligent Transportation Systems, 2021.

[12] Z. Jian, S. Zhang, S. Chen, Z. Nan, and N. Zheng, “A global-local coupling two-stage path planning method for mobile robots,” IEEE Robot Autom Lett, vol. 6, no. 3, pp. 5349–5356, 2021.

[11] Z. Jian, S. Chen, S. Zhang, Y. Chen, and N. Zheng, “Multi-model-based local path planning methodology for autonomous driving: An integrated framework,” IEEE Transactions on Intelligent Transportation Systems, 2020.

[10] S. Chen, Y. Chen, S. Zhang, and N. Zheng, “A novel integrated simulation and testing platform for self-driving cars with hardware in the loop,” IEEE Transactions on Intelligent Vehicles, vol. 4, no. 3, pp. 425–436, 2019.

[9] S. Chen, Z. Jian, Y. Huang, Y. Chen, Z. Zhou, and N. Zheng, “Autonomous driving: cognitive construction and situation understanding,” Science China Information Sciences, vol. 62, no. 8, pp. 1–27, 2019.（第六届中国科协优秀科技论文提名）
[8] J. Wang，N. Zheng，Wang, Fei-Yue，B. Chen，P. Chen，B. Xi，S. Chen，Z Liu, “Multivariate correlation entropy and law discovery in large data sets,” IEEE Intell Syst, vol. 33, no. 5, pp. 47–54, 2018.

[7] K. Yi, Z. Jian, S. Chen, and N. Zheng, “Feature selective small object detection via knowledge-based recurrent attentive neural network,” arXiv preprint arXiv:1803.05263, 2018.

[6] K. Yi, Z. Jian, S. Chen, Y. Chen, and N. Zheng, “Knowledge-based recurrent attentive neural network for traffic sign detection,” arXiv preprint arXiv:1803.05263, 2018.

[5] S. Chen, S. Zhang, J. Shang, B. Chen, and N. Zheng, “Brain-inspired cognitive model with attention for self-driving cars,” IEEE Trans Cogn Dev Syst, vol. 11, no. 1, pp. 13–25, 2017. （Outstanding Paper Award，杰出论文奖）

[4] J. Wang, Y. Ma, S. Chen, Z. Liu, and N. Zheng, “Fragmented knowledge processing and networked artificial intelligence,” Scientia Sinica (Informationis), vol. 47, no. 2, pp. 171–192, 2017.

[3] W. Jianji, M. Yongqiang, S. Chen, L. I. U. Ziyi, and N. ZHENG, “Fragmentation knowledge processing and networked artificial intelligence,” SCIENTIA SINICA Informationis, vol. 47, no. 2, pp. 171–192, 2017.

[2] S. Chen, L. I. U. Ziyi, N. ZHENG, and others, “Fragmentation knowledge processing and networked artificial intelligence” SCIENTIA SINICA Informationis, vol. 47, no. 2, pp. 171–192, 2017
[1] Nan-ning，ZHENG，Zi-yi，LIU，Peng-ju，REN，Yong-qiang，MA，S. Chen,CHEN，Si-yu，YU，Jian-ru，XUE，Ba-dong，CHEN，Fei-yue，WANG, “Hybrid-augmented intelligence: collaboration and cognition,” Frontiers of Information Technology & Electronic Engineering, vol. 18, no. 2, pp. 153–179, 2017.

Publications

[32]Z. Jian, S. Zhang, J. Zhang, S. Chen, and N. Zheng, “Parametric Path Optimization for Wheeled Robots Navigation,” in 2022 International Conference on Robotics and Automation (ICRA), 2022, pp. 10883–10889.

[31]J. Yang, T. Xiao, S. Zhang, S. Chen, and N. Zheng, “An Interactive Three-Dimensional Motion Simulation Method for Indoor Multi-Agent,” in 2021 China Automation Congress (CAC), 2021, pp. 6100–6105.   

[30]L. Tao, S. Zhang, S. Chen, and N. Zheng, “Multi-AGV pathfinding for automatic warehouse applications,” in 2021 China Automation Congress (CAC), 2021, pp. 7194–7199.

[29]D. Zhu, Y. Huang, S. Wang, S. Chen, Z. Nan, and N. Zheng, “MPR-Net: Multi-Scale Key Points Regression for Lane Detection,” in 2021 IEEE Intelligent Vehicles Symposium (IV), 2021, pp. 1457–1463.

 [28]Y. Shen, C. Xia, Z. Jian, S. Chen, and N. Zheng, “An Integrated Localization System with Fault Detection, Isolation and Recovery for Autonomous Vehicles,” in 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021, pp. 84–91.    

[27]Q. Hou, S. Zhang, S. Chen, Z. Nan, and N. Zheng, “Straight Skeleton Based Automatic Generation of Hierarchical Topological Map in Indoor Environment,” in 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021, pp. 2229–2236.

[26]K. Zhu,R. Huang,S. Chen,T. Xiao,Z. Zhu,X. Cheng,N. Zheng , “Pose Correction of Autonomous Vehicles with Edge Computing,” in 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021, pp. 143–148.

[25]Z. Jian, S. Zhang, S. Chen, T. Zhang, Z. Nan, and N. Zheng, “Obstacle-Centered Trajectory Planning for Autonomous Mobile Robot,” in 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021, pp. 486–492.

[24]D. You, S. Zhang, S. Chen, and N. Zheng, “A Novel 3D Point Cloud Registration Algorithm Based on Hybrid Line Features,” in 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021, pp. 2221–2228.

[23]R. Huang, K. Zhu, S. Chen, T. Xiao, M. Yang, and N. Zheng, “A High-precision and Robust Odometry Based on Sparse MMW Radar Data and A Large-range and Long-distance Radar Positioning Data Set,” in 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021, pp. 98–105.

[22]X. Yan, Y. Huang, S. Chen, Z. Nan, J. Xin, and N. Zheng, “DSP-Net: Dense-to-Sparse Proposal Generation Approach for 3D Object Detection on Point Cloud,” in 2021 International Joint Conference on Neural Networks (IJCNN), 2021, pp. 1–8.

[21] Y. Chen, S. Chen, T. Xiao, S. Zhang, Q. Hou, and N. Zheng, “Mixed test environment-based vehicle-in-the-loop validation-a new testing approach for autonomous vehicles,” in 2020 IEEE intelligent vehicles symposium (IV), 2020, pp. 1283–1289.

[20] T. Yang, Z. Nan, H. Zhang, S. Chen, and N. Zheng, “Traffic agent trajectory prediction using social convolution and attention mechanism,” in 2020 IEEE Intelligent Vehicles Symposium (IV), 2020, pp. 278–283.

[19]S. Xie, S. Chen, M. Tomizuka, N. Zheng, and J. Wang, “To Develop Human-like Automated Driving Strategy Based on Cognitive Construction: Appraisal and Perspective,” in 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), 2020, pp. 1–8.

[18]S. Xie, S. Chen, N. Zheng, and J. Wang, “Modeling methodology of driver-vehicle-environment system dynamics in mixed driving situation,” in 2020 IEEE Intelligent Vehicles Symposium (IV), 2020, pp. 1984–1991.

[17]Z. Xu, Y. Huang, S. Chen, Z. Nan, and N. Zheng, “Anchor-free pedestrain detection model with semantic context of traffic scenario,” in 2020 Chinese Automation Congress (CAC), 2020, pp. 1992–1997.

[16]Z. Zhou, S. Chen, R. Huang, and N. Zheng, “Robust 3d detection in traffic scenario with tracking-based coupling system,” in IFIP International Conference on Artificial Intelligence Applications and Innovations, 2020, pp. 330–339.

[15] Y. Yang, C. Xia, X. Deng, Y. Shen, S. Chen, and N. Zheng, “HeLPS: Heterogeneous LiDAR-based positioning system for autonomous vehicle,” in IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society, 2020, pp. 618–625.

[14]Z. Yang ,Y. Huang,X. Yan,S. Chen, “MuRF-Net: Multi-Receptive Field Pillars for 3D Object Detection from Point Cloud,” in 2020 IEEE Intelligent Vehicles Symposium (IV), 2020, pp. 1072–1079.

[13] K. Zhu ,J. Zhan,S. Chen,Z. Nan,T. Zhang,D. Zhu,N. Zheng, “ATV Navigation in Complex and Unstructured Environment Containing Stairs,” in 2020 IEEE Intelligent Vehicles Symposium (IV), 2020, pp. 817–824.

[12] P. Xue, J. Liu, S. Chen, Z. Zhou, Y. Huo, and N. Zheng, “Crossing-road pedestrian trajectory prediction via encoder-decoder lstm,” in 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2019, pp. 2027–2033.

[11] Y. Huo, Z. Xu, S. Chen, Y. Chen, Y. Huang, and N. Zheng, “SqueezeDet-Based Nighttime Traffic Light Detection with Filtering Rules,” in 2019 2nd China Symposium on Cognitive Computing and Hybrid Intelligence (CCHI), 2019, pp. 285–291.

[10] Z. Jian, S. Zhang, S. Chen, X. Lv, and N. Zheng, “High-definition map combined local motion planning and obstacle avoidance for autonomous driving,” in 2019 IEEE Intelligent Vehicles Symposium (IV), 2019, pp. 2180–2186.

[9] S. Zhang, Y. Chen, S. Chen, and N. Zheng, “Hybrid A*-based Curvature Continuous Path Planning in Complex Dynamic Environments,” in 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2019, pp. 1468–1474. （Best Student Paper Award，最佳学生论文）

[8] T. Zhang, S. Zhang, Y. Chen, C. Xia, S. Chen, and N. Zheng, “Mixture modules based intelligent control system for autonomous driving,” in IFIP International Conference on Artificial Intelligence Applications and Innovations, 2019, pp. 92–104.

[7] Z. Feng, S. Chen, Y. Chen, and N. Zheng, “Model-based decision making with imagination for autonomous parking,” in 2018 IEEE Intelligent Vehicles Symposium (IV), 2018, pp. 2216–2223.

[6] C. Xia ,C. Xia,Y. Shen,T. Zhang,S. Zhang,Y. Huo,S. Chen,N. Zheng, “Robust Extrinsic Parameter Calibration of 3D LIDAR Using Lie Algebras,” in 2019 IEEE Intelligent Vehicles Symposium (IV), 2019, pp. 1775–1781.

[5] Y. Chen, S. Chen, T. Zhang, S. Zhang, and N. Zheng, “Autonomous vehicle testing and validation platform: Integrated simulation system with hardware in the loop,” in 2018 IEEE Intelligent Vehicles Symposium (IV), 2018, pp. 949–956. （Best Student Paper Award，最佳学生论文）

[4] K. Yi, S. Chen, Y. Chen, C. Xia, and N. Zheng, “Cognition-based deep learning: Progresses and perspectives,” in IFIP International Conference on Artificial Intelligence Applications and Innovations, 2018, pp. 121–132.

[3] Y. Huang, S. Chen, Y. Chen, Z. Jian, and N. Zheng, “Spatial-temproal based lane detection using deep learning,” in IFIP International conference on artificial Intelligence applications and innovations, 2018, pp. 143–154.

[2] J. Jiang, P. Xue, S. Chen, Z. Liu, X. Zhang, and N. Zheng, “Line feature based extrinsic calibration of LiDAR and camera,” in 2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES), 2018, pp. 1–6.

[1] S. Chen, J. Shang, S. Zhang, and N. Zheng, “Cognitive map-based model: Toward a developmental framework for self-driving cars,” in 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), 2017, pp. 1–8