Led by Prof. Zhiqiang Zheng, our NuBot team was founded in 2004. Currently we have two full professors (Prof. Zhiqiang Zheng and Prof. Hui Zhang), one associate professor (Prof. Huimin Lu), one assistant professor (Dr. Junhao Xiao), and several graduate students. Till now, 8 team members have obtained their doctoral degree with the research on RoboCup Middle Size League (MSL), and more than 20 have obtained their master degrees. For more detail of each member please see NuBoters.
As shown in the figure below, five generations of robots have been created since 2004. We participated in RoboCup Simulation and Small Size League (SSL) initially. Since 2006, we have been participating in RoboCup MSL actively, e.g., we have been to Bremen, Germany (2006), Atlanta, USA (2007), Suzhou, China (2008), Graz, Austria (2009), Singapore (2010), Eindhoven, Netherlands (2013), Joao Pessoa, Brazil (2014), Hefei, China (2015) and Leipzig Germany (2016). We have also been participating in RoboCup China Open since it was launched in 2006.
The NuBot robots have been employed not only for RoboCup, but also for other research as an ideal test bed more than robot soccer. As a result, we have published more than 70 journal papers and conference papers. For more detail please see the publication list. Our current research mainly focuses on multi-robot coordination, robust robot vision and formation control.
The following items are our team description papers (TDPs) which illustrates our research progress over the past years.
Bo Sun, Yadan Zeng, Houde Dai, JunhaoXiao, Jianwei Zhang, (2017) "A novel scan registration method based on the feature-less global descriptor – spherical entropy image", Industrial Robot: An International Journal, Vol. 44 Issue: 4, pp.552-563.
Junhao Xiao, Dan Xiong, Weijia Yao, Qinghua Yu, Huimin Lu, Zhiqiang Zheng, Building Software System and Simulation Environment for RoboCup MSL Soccer RobotsBased on ROS and Gazebo, Springer Book on Robot Operating System (ROS) –The Complete Reference (Volume 2), pp. 597-631, 2017.
Sha Luo, Weijia Yao, Qinghua Yu, Junhao Xiao, Huimin Lu and Zongtan Zhou. Object Detection Based on GPU Parallel Computing for RoboCup Middle Size League. Proceedings of the 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO 2017), Macau, 2017.
Minjun Xiong, Huimin Lu, Dan Xiong, Junhao Xiao, Ming Lv. Scale-Aware Monocular Visual-Inertial Pose Estimation for Aerial Robots. Chinese Automation Congress 2017, Jinan, 2017.
Sha Luo, Huimin Lu, Junhao Xiao, Qinghua Yu, Zhiqiang Zheng. Robot Detection and Localization Based on Deep Learning. Chinese Automation Congress 2017, Jinan, 2017.
Pan Wang, Junhao Xiao, Huimin Lu, Hui Zhang, Ruoyi Yan, Shaozun Hong. A Novel Human-Robot Interaction System Based on 3D Mapping and Virtual Reality. Chinese Automation Congress 2017, Jinan, 2017.
Xieyuanli Chen, Hui Zhang, Huimin Lu, Junhao Xiao, Qihang Qiu and Yi Li. Robust SLAM system based on monocular vision and LiDAR for robotic urban search and rescue. Proceedings of the 15th IEEE International Symposium on Safety, Security, and Rescue Robotics 2017 (SSRR 2017), Shanghai, 2017.
Xieyuanli Chen, Huimin Lu, Junhao Xiao, Hui Zhang, PanWang. Robust relocalization based on active loop closure for real-time monocular SLAM. Proceedings of the 11th International Conference on Computer Vision Systems (ICVS), 2017.
Weijia Yao, Zhiwen Zeng, Xiangke Wang, Huimin Lu, Zhiqiang Zheng. Distributed Encirclement Control with Arbitrary Spacing for Multiple Anonymous Mobile Robots. Proceedings of the 36th Chinese Control Conference, 2017.
Zhiwen Zeng, Xiangke Wang, Zhiqiang Zheng, et al. Edge Agreement of Second-order Multi-agent System with Dynamic Quantization via Directed Edge Laplacian. Nonlinear Analysis: Hybrid Systems, Vol. 23, pp. 1-10, 2017.
Yuhua Zhong, Junhao Xiao, Huimin Lu, Hui Zhang. Real-Time Terrain Classification for Rescue Robot Based on Extreme Learning Machine. In: Sun F., Liu H., Hu D. (eds) Cognitive Systems and Signal Processing. ICCSIP 2016. Communications in Computer and Information Science, vol 710, 2017. Springer, Singapore.
卢惠民，肖军浩，郑志强，ROS与中型组足球机器人，国防工业出版社，ISBN: 978-7-118-10952-8，31.7万字, 2016.10.
肖军浩，机器人操作系统浅析(译)，国防工业出版社，10万字，ISBN: 978-7-118-11056-2，18万字, 2016.09.
Lilian Zhang, Huimin Lu, Xiaoping Hu, Reinhard Koch. Vanishing Point Estimation and Line Classification in a Manhattan World with a Unifying Camera Model. International Journal of Computer Vision, Vol. 117, No. 2,pp. 111-130, 2016.
Dan Xiong, Junhao Xiao, Huimin Lu, Zhiwen Zeng, Qinghua Yu, Kaihong Huang, Xiaodong Yi, Zhiqiang Zheng.The design of an intelligent soccer-playing robot. Industrial Robot: An International Journal, Vol. 43, No.1, pp. 91-102, 2016. [PDF]
Huimin Lu, Lixing Jiang, Andreas Zell. Long Range Traversable Region Detection Based on Superpixels Clustering for Mobile Robots. Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2015), Hamburg, Germany, September 28~October 02, 2015, pp. 546-552. [PDF]
Shuai Cheng, Junhao Xiao, Huimin Lu. Real-time obstacle avoidance using subtargets and Cubic B-spline for mobile robots. Proceedings of 2014 IEEE International Conference on Information and Automation, China, 2014, pp. 634-639.[PDF]
Xun Li, Huimin Lu, Dan Xiong, Hui Zhang and Zhiqiang Zheng. A Survey on Visual Perception for RoboCup MSL Soccer Robots. International Journal of Advanced Robotic Systems, Vol.10, 110:2013, pp.1-10, 2013. [PDF]
Huimin Lu, Xun Li, Hui Zhang, and Zhiqiang Zheng. Robust Place Recognition Based on Omnidirectional Vision and Real-time Local Visual Features for Mobile Robots. Advanced Robotics, Vol.27, No.18, pp.1439-1453, 2013. [PDF]
Huimin Lu, Xun Li, Hui Zhang, Mei Hu and Zhiqiang Zheng. Robust and Real-time Self-Localization Based on Omnidirectional Vision for Soccer Robots. Advanced Robotics, Vol.27, No.10, pp.799-811, 2013. [PDF]
Zhiwen Zeng, Huimin Lu, Zhiqiang Zheng. High-speed Trajectory Tracking Based on Model Predictive Control for Omni-directional Mobile Robots. Proceedings of the 2013 25th Chinese Control and Decision Conference (CCDC), Guiyang, China, May 25-27, 2013, pp. 3179-3184. [PDF]
Hui Zhang, Huimin Lu, Peng Dong, Dan Xiong, and Zhiqiang Zheng. A Novel Generic Ball Recognition Algorithm Based on Omnidirectional Vision for Soccer Robots. International Journal of Advanced Robotic Systems, Vol. 10, 388:2013, pp. 1-12, 2013. [PDF]
YU Qinghua, HUANG Kaihong, LU Huimin, GUO Hongwu. Object Motion Estimation and Interception Based on Stereo Vision for Soccer Robots in 3D Space. Proceedings of the 32nd Chinese Control Conference, Xi'an, China, July 26-28, 2013, pp. 5943-5948. [PDF]
Dan Xiong, Huimin Lu, Zhiwen Zeng, Zhiqiang Zheng. Topological Localization Based on Key-frames Selection and Vocabulary Tree for Mobile Robots. Proceeding of the IEEE International Conference on Robotics and Biomimetics (ROBIO), Shenzhen, China, December 2013, pp. 2505-2510.
Dan Xiong, Huimin Lu, Zhiqiang Zheng. A self-localization method based on omnidirectional vision and MTi for soccer robots. Proceedings of the 10th World Congress on Intelligent Control and Automation, Beijing, China, 2012, pp. 3731-3736. [PDF]
Huimin Lu, Shaowu Yang, Hui Zhang, Zhiqiang Zheng. A Robust Omnidirectional Vision Sensor for Soccer Robots. Mechatronics, Elsevier, Vol.21, No.2, pp. 373-389, 2011. [PDF]
Huimin Lu, Hui Zhang, Zhiqiang Zheng. A Novel Real-Time Local Visual Feature for Omnidirectional Vision Based on FAST and LBP. RoboCup 2010: Robot Soccer World Cup XIV, LNAI 6556, Springer, pp. 291-302, 2011. [PDF]
Huimin Lu, Zhiqiang Zheng. Two Novel Real-Time Local Visual Features for Omnidirectional Vision. Pattern Recognition, Elsevier, Vol.43, No.12, pp. 3938-3949, 2010. [PDF]
Huimin Lu, Hui Zhang, Shaowu Yang, Zhiqiang Zheng. Camera Parameters Auto-Adjusting Technique for Robust Robot Vision. Proceedings of the 2010 IEEE International Conference on Robotics and Automation (ICRA 2010), Anchorage, Alaska, USA, May 5~8, 2010, pp. 1518-1523. [PDF]
Xiangke Wang, Hui Zhang, Huimin Lu, Zhiqiang Zheng. A New Triple-based Multi-robot System Architecture and Application in Soccer Robots. ICIRA 2010, Part II, LNAI 6425, Springer, pp. 105-115, 2010. [PDF]
卢惠民, 张辉, 杨绍武, 郑志强. 一种鲁棒的基于全向视觉的足球机器人自定位方法. 机器人, Vol.32, No.4, pp. 553-559+567, 2010. [PDF]
Huimin Lu, Hui Zhang, Shaowu Yang, Zhiqiang Zheng. A Novel Camera Parameters Auto-Adjusting Method Based on Image Entropy. RoboCup 2009: Robot Soccer World Cup XIII, LNAI 5949, Springer, pp. 192-203, 2010. [PDF]
Huimin Lu, Hui Zhang, Shaowu Yang, Zhiqiang Zheng. Vision-based Ball Recognition for Soccer Robots without Color Classification. Proceedings of 2009 IEEE International Conference on Information and Automation, Zhuhai/Macau,China, 2009, pp. 916-921. [PDF]
卢惠民, 张辉, 郑志强. 基于视觉的移动机器人自定位问题. 中南大学学报（自然科学版）, Vol.40, Suppl.1, pp. 127-134, 2009.
Huimin Lu, Hui Zhang, Junhao Xiao, Fei Liu, Zhiqiang Zheng. Arbitrary Ball Recognition Based on Omni-directional Vision for Soccer Robots. RoboCup 2008: Robot Soccer World Cup XII, LNAI 5399, Springer, pp. 133-144, 2009.[PDF]
Huimin Lu, Zhiqiang Zheng, Fei Liu, Xiangke Wang. A Robust Object Recognition Method for Soccer Robots.Proceedings of 7th World Congress on Intelligent Control and Automation,Chongqing,China, 2008, pp. 1645-1650. [PDF]
刘斐, 卢惠民, 郑志强. 基于线性分类器的混合空间查找表颜色分类方法. 中国图象图形学报, Vol.13, No.1, pp. 104-108, 2008.
柳林, 刘斐, 季秀才, 卢惠民, 海丹, 郑志强. 全向移动机器人编队分布式控制研究. 机器人, Vol. 29, No.1, pp. 23-28, 2007.
Fei Liu, Huimin Lu, Zhiqiang Zheng. A Robust Approach of Field Features Extraction for Robot Soccer. Proceedings of 4th IEEE LARS 07/COMRob 07, ROBOTIC FORUM Monterrey 2007, November 05-09, 2007.
卢惠民, 刘斐, 郑志强. 一种新的用于足球机器人的全向视觉系统. 中国图象图形学报, Vol.12, No.7, pp. 1243-1248, 2007.
Fei Liu, Huimin Lu, Zhiqiang Zheng. A Modified Color Look-Up Table Segmentation Method for Robot Soccer. Proceedings of 4th IEEE LARS 07/COMRob 07, ROBOTIC FORUM Monterrey 2007, November 05-09, 2007.
卢惠民, 王祥科, 刘斐, 季秀才, 郑志强. 基于全向视觉和前向视觉的足球机器人目标识别. 中国图象图形学报, Vol.11, No.11, pp. 1686-1689, 2006.
Xiucai Ji, Lin Liu and Zhiqiang Zheng. A modular hierarchical architecture for autonomous robots based on task-driven behaviors. International Conference on Sensing, Computing and Automation, Chongqing, China, May 8-11, 2006: 631~636.
柳林, 季秀才, 郑志强. 基于市场法及能力分类的多机器人任务分配研究. 机器人, 2006, 28(3): 337~343.
LIU Lin and ZHENG Zhiqiang. Combinatorial bids based multi-robot task allocation method. Proceedings of the 2005 IEEE International Conference on Robotics and Automation（ICRA2005）, 2005: 1157~1162.
LIU Lin and ZHENG Zhiqiang. A novel multi-robot coordination method using capability category. Proceedings of the 16th IFAC World Congress, 2005.
LIU Lin, WANG Lei, ZHENG Zhiqiang, SUN Zengqi. A learning market based layered multi-robot architecture. Proceedings of the 2004 IEEE International Conference on Robotics and Automation（ICRA2004）, 2004: 3417~3422.
柳林, 郑志强. 多机器人任务分配及其在机器人足球中的应用. 控制理论与应用, 2004, 21(Suppl.): 46~50.
This video is about the experimental results of the following paper: Xieyuanli Chen, Hui Zhang, Huimin Lu, Junhao Xiao, Qihang Qiu and Yi Li. Robust SLAM system based on monocular vision and LiDAR for robotic urban search and rescue. Proceedings of the 15th IEEE International Symposium on Safety, Security, and Rescue Robotics 2017 (SSRR 2017), Shanghai, 2017
Abstract. In this paper, we propose a monocular SLAM system for robotic urban search and rescue (USAR). Based on it, most USAR tasks (e.g. localization, mapping, exploration and object recognition) can be fulfilled by rescue robots with only a single camera. The proposed system can be a promising basis to implement fully autonomous rescue robots. However, the feature-based map built by the monocular SLAM is difficult for the operator to understand and use. We therefore combine the monocular SLAM with a 2D LiDAR SLAM to realize a 2D mapping and 6D localization SLAM system which can not only obtain a real scale of the environment and make the map more friendly to users, but also solve the problem that the robot pose cannot be tracked by the 2D LiDAR SLAM when the robot climbing stairs and ramps. We test our system using a real rescue robot in simulated disaster environments. The experimental results show that good performance can be achieved using the proposed system in the USAR. The system has also been successfully applied in the RoboCup Rescue Robot League (RRL) competitions, where our rescue robot team entered the top 5 and won the Best in Class Small Robot Mobility in 2016 RoboCup RRL Leipzig Germany, and the champions of 2016 and 2017 RoboCup China Open RRL.
Founder and director
Prof. Dr. Zhiqiang Zheng
Prof. Dr. Hui Zhang
Associate Prof. Dr. Huimin Lu
Dr. Junhao Xiao
Sha Luo (female)
Minjun Xiong (female)
Ruoyi Yan (female)
Dr. Lin Liu
Dr. Fei Liu
Dr. Xiucai Ji
Associate Prof. Dr. Wenjie Shu
Dr. Dan Hai
Associate Prof. Dr. Xiangke Wang
Dr. Shaowu Yang
Dr. Lina Geng (female)
Dr. Shuai Tang
Dr. Zhiwen Zeng
Dr. Xiabin Dong
Mrs. Wei Liu
Mr. Yupeng Liu
Mr. Dachuan Wang
Mr. Baifeng Yu
Mr. Fangyi Sun
Mr. Lianhu Cui
Mr. Shengcai Lu
Mr. Peng Dong
Mr. Yubo Li
Mr. Xiaozhou Zhu
Mr. Qingzhu Cui
Mr. Xingrui Yang
Mr. Kaihong Huang
Mr. Shuai Cheng
Mr. Xiaoxiang Zheng
Mr. Yunlei Chen
Mr. Xianglin Yang
Mr. Yu Zhang
Mrs. Yaoyao Lan
Mr. Yuxi Huang
Mr. Yi Liu
Mr. Yuhua Zhong
Mr. Qiu Cheng
Supported by National University of Defense Technology, our team has designed the NuBot rescue robot from the mechanical structure to the electronic architecture and software system. Benefiting from the strong mechanical structure, our rescue robot has good mobility and is quite durable, so it will not be trapped even facing the highly cluttered and unstructured terrains in the urban search and rescue. The electronic architecture is built based on industrial standards which can bear electromagnetic interference and physical impact from the intensive tasks. The software system is developed upon the Robot Operating System (ROS). Based on self-developed programs and several basic open source packages provided in the ROS, we developed a complete software system including the localization, mapping, exploration, object recognition, etc. Our robot system has been successfully applied and tested in the RoboCup Rescue Robot League (RRL) competitions, where our rescue robot team entered the top 5 and won the Best in Class small robot mobility in 2016 RoboCup RRL Leipzig Germany, and won the champions of 2016 and 2017 RoboCup China Open RRL competitions.
The following pictures show that our rescue robot participated in RoboCup 2016 RRL competition.
This video is about the experimental results of the following paper: Xieyuanli Chen, Huimin Lu, Junhao Xiao, Hui Zhang, Pan Wang. Robust relocalization based on active loop closure for real-time monocular SLAM. Proceedings of the 11th International Conference on Computer Vision Systems (ICVS), 2017.
Abstract. Remarkable performance has been achieved using the state-of-the-art monocular Simultaneous Localization and Mapping (SLAM) algorithms. However, tracking failure is still a challenging problem during the monocular SLAM process, and it seems to be even inevitable when carrying out long-term SLAM in large-scale environments. In this paper, we propose an active loop closure based relocalization system, which enables the monocular SLAM to detect and recover from tracking failures automatically even in previously unvisited areas where no keyframe exists. We test our system by extensive experiments including using the most popular KITTI dataset, and our own dataset acquired by a hand-held camera in outdoor large-scale and indoor small-scale real-world environments where man-made shakes and interruptions were added. The experimental results show that the least recovery time (within 5ms) and the longest success distance (up to 46m) were achieved comparing to other relocalization systems. Furthermore, our system is more robust than others, as it can be used in different kinds of situations, i.e., tracking failures caused by the blur, sudden motion and occlusion. Besides robots or autonomous vehicles, our system can also be employed in other applications, like mobile phones, drones, etc.
This video is the accompanying video for the following paper: Weijia Yao, Zhiwen Zeng, Xiangke Wang, Huimin Lu, Zhiqiang Zheng. Distributed Encirclement Control with Arbitrary Spacing for Multiple Anonymous Mobile Robots. Proceedings of the 36th Chinese Control Conference, 2017.
Abstract: Encirclement control enables a multi-robot system to rotate around a target while they still preserve a circular formation, which is useful in real world applications such as entrapping a hostile target. In this paper, a distributed control law is proposed for any number of anonymous and oblivious robots in random three dimensional positions to form a specified circular formation with any desired inter-robot angular distances (i.e. spacing) and encircle around the target. Arbitrary spacing is useful for a system composed of heterogeneous robots which, for example, possess different kinematics capabilities, since the spacing can be designed manually for any specific purpose. The robots are modelled by single-integrator models, and they can only sense the angular positions of their two neighboring robots, so the control law is distributed. Theoretical analysis and simulation results are provided to prove the stability and effectiveness of the proposed control strategy.
1. Real Robot Code
2. Simulation System Based on ROS and Gazebo
Single robot simulation demo: https://github.com/nubot-nudt/single_nubot_gazebo
Multi-robot simulation: https://github.com/nubot-nudt/gazebo_visual
Simatch for China Robot Competition: https://github.com/nubot-nudt/simatch
Note: The last option is an integration of every components needed for a complete simulation. So it is recommended to download it for multi-robot coordination research. There are English documentation and some Chinese comments.
3. Coach for Simulation
Anyone is welcome to download and use them. :)