Crowd navigation has becoming an increasingly prominent problem in robotics. The main challenge comes from the lack of understanding of pedestrians’ behaviors. Encouraged by the great achievement in trajectory prediction, the twin field of crowd navigation, this work focus on integrating trajectory prediction with path planning and proposed a crowd navigation algorithm named RHC-T (Receding Horizon Control with Trajjectron++). It consists of two independent modules: one for trajectory prediction and another for receding horizon control. Benefiting from the trajectory prediction module, RHC-T builds up an explicit understanding of pedestrians’behaviors in the form of predicted trajectories. Base on the formulation of receding horizon control, the proposed algorithm can deal with the time-varying obstacle constraints from pedestrians, naturally. Furthermore, extensive experiments are performed on two pedestrian trajectory datasets, ETH and UCY, to evaluate the proposed algorithm in a more realistic way than previous works. Experimental results show that RHC-T reduces the intervention to pedestrians significantly and navigates the robot in time-efficient paths. Compared with three baseline algorithms, RHC-T achieves better performance with an improvement in the intervention rate and navigation time of at least 8.00% and 3.88%, respectively.
This video is the accompanying video of the paper: Jiayang Liu, Junhao Xiao, Huimin Lu, Zhiqian Zhou, Sichao Lin, Zhiqiang Zheng. Terrain Assessment Based on Dynamic Voxel Grids in Outdoor Unstructured Environments
Abstract: For ground robots working in outdoor unstructured environments, terrain assessment is a key step for path planning.In this paper, we propose a novel terrain assessment method. The raw 3D point clouds are segmented based on dynamic voxel grids, then the untraversable areas are extracted and stored in the form of 2D occupancy grid maps. Afterwards, only the traversable areas are processed and stored in the form of 2.5D digital elevation maps (DEMs). In this case, the efficiency of the terrain assessment is improved and the query space of terrain feature information is reduced. To evaluate the proposed algorithm, the approach operating on point clouds has served as the baseline. According to the experimental results, our method has a better performance in both assessment time and query efficiency.
The team description paper can be downloaded from here.
[1] Wei Dai, Huimin Lu, Junhao Xiao and Zhiqiang Zheng. Task Allocation without Communication Based on Incomplete Information Game Theory for Multi-robot Systems. Journal of Intelligent & Robotic Systems, 2018. [PDF]
3rd place in MSL scientific challenge in RoboCup 2019, Sydney, Australia
1st place in MSL technique challenge in RoboCup 2019, Sydney, Australia
4th place in MSL of RoboCup 2019, Sydney, Australia
2018
4th place in MSL scientific challenge in RoboCup 2018, Montréal, Canada
3st place in MSL technique challenge in RoboCup 2018, Montréal, Canada
4th place in MSL of RoboCup 2018, Montréal, Canada
2nd place in MSL of RoboCup 2018 ChinaOpen, ShaoXing, China
2nd place in MSL technique challenge of RoboCup 2018 ChinaOpen,ShaoXing, China
3rd place in MSL scientific challenge in RoboCup 2017, Nagoya, Japan
3rd place in MSL technique challenge in RoboCup 2017, Nagoya, Japan
4th place in MSL of RoboCup 2017, Nagoya, Japan
3rd place in MSL of RoboCup 2017 ChinaOpen, RiZhao, China
1st place in MSL scientific challenge of RoboCup 2017 ChinaOpen, RiZhao, China
4. Qualification video
The qualification video for RoboCup 2021 (Virtual) can be found at our youku channel(recommended for users in China) or our YouTube channel (recommended for users out of China).
5. Mechanical and Electrical Description and Software Flow Chart
NuBot Team Mechanical and Electrical Description together with a Software Flow Chart can be downloaded from here.
Zhiqian Zhou, one member of NuBot team, served to MSL community as a member of OC RoboCup 2019 Syndey and TC RoboCup 2020 Bordeaux, France.
We built a dataset for robot detection which contained fully annotated images acquired from MSL competitions. The dataset is publicly available at: https://github.com/Abbyls/robocup-MSL-dataset
7. Declaration regarding mixed team
No!
8. Declaration regarding 802.11b AP
No!
9. MAC address
The list of our team's MAC addresses can be downloaded from here.
The team description paper can be downloaded from here.
[1] Wei Dai, Huimin Lu, Junhao Xiao and Zhiqiang Zheng. Task Allocation without Communication Based on Incomplete Information Game Theory for Multi-robot Systems. Journal of Intelligent & Robotic Systems, 2018. [PDF]
3rd place in MSL scientific challenge in RoboCup 2019, Sydney, Australia
1st place in MSL technique challenge in RoboCup 2019, Sydney, Australia
4th place in MSL of RoboCup 2019, Sydney, Australia
2018
4th place in MSL scientific challenge in RoboCup 2018, Montréal, Canada
3st place in MSL technique challenge in RoboCup 2018, Montréal, Canada
4th place in MSL of RoboCup 2018, Montréal, Canada
2nd place in MSL of RoboCup 2018 ChinaOpen, ShaoXing, China
2nd place in MSL technique challenge of RoboCup 2018 ChinaOpen,ShaoXing, China
3rd place in MSL scientific challenge in RoboCup 2017, Nagoya, Japan
3rd place in MSL technique challenge in RoboCup 2017, Nagoya, Japan
4th place in MSL of RoboCup 2017, Nagoya, Japan
3rd place in MSL of RoboCup 2017 ChinaOpen, RiZhao, China
1st place in MSL scientific challenge of RoboCup 2017 ChinaOpen, RiZhao, China
4. Qualification video
The qualification video for RoboCup 2021 Bordeaux, France can be found at our youku channel(recommended for users in China) or our YouTube channel (recommended for users out of China).
5. Mechanical and Electrical Description and Software Flow Chart
NuBot Team Mechanical and Electrical Description together with a Software Flow Chart can be downloaded from here.
Zhiqian Zhou, one member of NuBot team, served to MSL community as a member of OC RoboCup 2019 Syndey and TC RoboCup 2020 Bordeaux, France.
We built a dataset for robot detection which contained fully annotated images acquired from MSL competitions. The dataset is publicly available at: https://github.com/Abbyls/robocup-MSL-dataset
7. Declaration regarding mixed team
No!
8. Declaration regarding 802.11b AP
No!
9. MAC address
The list of our team's MAC addresses can be downloaded from here.
The team description paper can be downloaded from here.
[1] Wei Dai, Huimin Lu, Junhao Xiao and Zhiqiang Zheng. Task Allocation without Communication Based on Incomplete Information Game Theory for Multi-robot Systems. Journal of Intelligent & Robotic Systems, 2018. [PDF]
3rd place in MSL scientific challenge in RoboCup 2019, Sydney, Australia
1st place in MSL technique challenge in RoboCup 2019, Sydney, Australia
4th place in MSL of RoboCup 2019, Sydney, Australia
2018
4th place in MSL scientific challenge in RoboCup 2018, Montréal, Canada
3st place in MSL technique challenge in RoboCup 2018, Montréal, Canada
4th place in MSL of RoboCup 2018, Montréal, Canada
2nd place in MSL of RoboCup 2018 ChinaOpen, ShaoXing, China
2nd place in MSL technique challenge of RoboCup 2018 ChinaOpen,ShaoXing, China
3rd place in MSL scientific challenge in RoboCup 2017, Nagoya, Japan
3rd place in MSL technique challenge in RoboCup 2017, Nagoya, Japan
4th place in MSL of RoboCup 2017, Nagoya, Japan
3rd place in MSL of RoboCup 2017 ChinaOpen, RiZhao, China
1st place in MSL scientific challenge of RoboCup 2017 ChinaOpen, RiZhao, China
4. Qualification video
The qualification video for RoboCup 2020 Bordeaux, France can be found at our youku channel(recommended for users in China) or our YouTube channel (recommended for users out of China).
5. Mechanical and Electrical Description and Software Flow Chart
NuBot Team Mechanical and Electrical Description together with a Software Flow Chart can be downloaded from here.
Zhiqian Zhou, one member of NuBot team, served to MSL community as a member of OC RoboCup 2019 Syndey and TC RoboCup 2020 Bordeaux, France.
We built a dataset for robot detection which contained fully annotated images acquired from MSL competitions. The dataset is publicly available at: https://github.com/Abbyls/robocup-MSL-dataset
7. Declaration regarding mixed team
No!
8. Declaration regarding 802.11b AP
No!
9. MAC address
The list of our team's MAC addresses can be downloaded from here.
This video is the accompanying video of the paper：Xiao Li, Bingxin Han, Zhiwen Zeng, Junhao Xiao, Huimin Lu. Human-Robot Interaction Based on Battle Management Language for Multi-robot System
Abstract: Commanding and controlling a multi-robot system is a challenging task. Static control commands are difficult to fully meet the requirements of controlling different robots. As the number of robots increases, it is difficult for the robot's motion-level commands to simultaneously satisfy the demands of commanding multi-robot system. This paper uses a limited natural language to control multi-robot systems, and proposes a framework based on Battle Management Language (BML) to command multi-robot systems. Based on the framework, the capabilities and names of the robot can be dynamically added to the dictionary, and the limited natural language can be converted into a standard BML command according to the dictionary to control the multi-robot system. In this way, the robot can execute motion-level commands, such as movement, steering, etc., and can also perform task-level commands, such as enclosing, defense, etc. The experimental results show that the system composed of different types of robots can be commanded by using the interactive framework proposed in this paper.
The team description paper can be downloaded from here, with the main contribution of a newly designed three-wheel robot.
[1] Wei Dai, Huimin Lu, Junhao Xiao and Zhiqiang Zheng. Task Allocation without Communication Based on Incomplete Information Game Theory for Multi-robot Systems. Journal of Intelligent & Robotic Systems, 2018. [PDF]
4th place in MSL scientific challenge in RoboCup 2018, Montréal, Canada
3rd place in MSL technique challenge in RoboCup 2018, Montréal, Canada
4th place in MSL of RoboCup 2018, Montréal, Canada
2nd place in MSL of RoboCup 2018 ChinaOpen, ShaoXing, China
2nd place in MSL technique challenge of RoboCup 2018 ChinaOpen, ShaoXing, China
3rd place in MSL scientific challenge in RoboCup 2017, Nagoya, Japan
3rd place in MSL technique challenge in RoboCup 2017, Nagoya, Japan
4th place in MSL of RoboCup 2017, Nagoya, Japan
3rd place in MSL of RoboCup 2017 ChinaOpen, RiZhao, China
1st place in MSL scientific challenge of RoboCup 2016 ChinaOpen, RiZhao, China
3rd place in MSL scientific challenge in RoboCup 2016, Leipzig, Germany
4th place in MSL of RoboCup 2016, Leipzig, Germany
3rd place in MSL of RoboCup 2016 ChinaOpen, Hefei, China
1st place in MSL scientific challenge of RoboCup 2016 ChinaOpen, Hefei, China
4. Qualification video
The qualification video for RoboCup 2019 Sydney, Australia can be found at our youku channel(recommended for users in China) or our YouTube channel (recommended for users out of China).
5. Mechanical and Electrical Description and Software Flow Chart
NuBot Team Mechanical and Electrical Description together with a Software Flow Chart can be downloaded from here.
Zhiqian Zhou, one member of Nubot team, served to MSL community as a member of OC RoboCup 2019 Sydney, Australia.
7. Declaration regarding mixed team
No!
8. Declaration regarding 802.11b AP
No!
9. MAC address
The list of our team's MAC addresses can be downloaded from here.
This video is about the experimental results of the following paper: Yi Li, Chenggang Xie, Huimin Lu, Xieyuanli Chen, Junhao Xiao and Hui Zhang. Scale-aware Monocular SLAM Based on Convolutional Neural Network. Proceedings of the 15th IEEE International Conference on Information and Automation 2018 ( ICIA 2018 ), Mount Wuyi, 2018.
Abstract—Remarkable performance has been achieved using the state-of-the-art monocular Simultaneous Localization and Mapping (SLAM) algorithms. However, due to the scale ambiguity limitation of monocular vision, the existing monocular SLAM systems can not directly restore the absolute scale in unknown environments. Given the amazing results in the field of depth estimation from Convolutional Neural Networks (CNNs), we propose a CNN-based monocular SLAM, where we naturally combine the CNN-predicted depth maps together with the monocular ORB-SLAM, overcoming the scale ambiguity limitation of the monocular SLAM. We test our method using the popular KITTI odometry benchmark, and the experimental results show that the overall performance of average translational and rotational error can reach 2.00% and 0.0051º/m. In addition, our approach can work well under the pure rotation motion, which shows the robustness and high accuracy of the proposed algorithm.
Abstract— Most robots in urban search and rescue (USAR) fulfill tasks teleoperated by human operators. The operator has to know the location of the robot and find the position of the target (victim). This paper presents an augmented reality system using a Kinect sensor on a customly designed rescue robot. Firstly, Simultaneous Localization and Mapping (SLAM) using RGB-D cameras is running to get the position and posture of the robot. Secondly, a deep learning method is adopted to obtain the location of the target. Finally, we place an AR marker of the target in the global coordinate and display it on the operator's screen to indicate the target even when the target is out of the camera’s field of view. The experimental results show that the proposed system can be applied to help humans interact with robots.
This video is the accompanying video of the paper: Junchong Ma, Weijia Yao, Wei Dai, Huimin Lu, Junhao Xiao, Zhiqiang Zheng. Cooperative Encirclement Control for a Group of Targets by Decentralized Robots with Collision Avoidance. Proceedings of the 37th Chinese Control Conference, 2018.
Abstract: This study focuses on multi-target capture and encirclement control problem for multiple mobile robots. With the distributed architecture, this problem involves a group of robots to encircle several moving targets in a coordinated circle formation. In order to efficiently allocate the targets to robots, a Hybrid Dynamic Task Allocation (HDTA) algorithm was proposed, in which a temporary "manager" robot was assigned to negotiate with other robots. For encirclement formation, a robust control law was introduced for any number of mobile robots to form a specific circle formation with arbitrary inter-robot angular spacing. In view of safety, an online collision avoidance algorithm combining the sub-targets and Artificial Potential Fields (APF) approaches was proposed, which ensures that the paths of robots are collision-free. To prove the validity and robustness of the proposed scheme, both theoretical analysis and simulation experiments were conducted.
The team description paper can be downloaded from here, with the main contribution of a newly designed three-wheel robot.
[1] Wei Dai, Huimin Lu, Junhao Xiao and Zhiqiang Zheng. Task Allocation without Communication Based on Incomplete Information Game Theory for Multi-robot Systems. Journal of Intelligent & Robotic Systems, 2018. [PDF]
3rd place in MSL scientific challenge in RoboCup 2017, Nagoya, Japan
3rd place in MSL technique challenge in RoboCup 2017, Nagoya, Japan
4th place in MSL of RoboCup 2017, Nagoya, Japan
3rd place in MSL of RoboCup 2017 ChinaOpen, RiZhao, China
1st place in MSL scientific challenge of RoboCup 2016 ChinaOpen, RiZhao, China
3rd place in MSL scientific challenge in RoboCup 2016, Leipzig, Germany
4th place in MSL of RoboCup 2016, Leipzig, Germany
3rd place in MSL of RoboCup 2016 ChinaOpen, Hefei, China
1st place in MSL scientific challenge of RoboCup 2016 ChinaOpen, Hefei, China
2rd place in MSL technique challenge in RoboCup 2015, Hefei, China
3rd place in MSL scientific challenge in RoboCup 2015, Hefei, China
6th place in MSL of RoboCup 2015, Hefei, China
4. Qualification video
The qualification video for RoboCup 2018 Montreal, Canada can be found at our youku channel (recommended for users in China) or our YouTube channel (recommended for users out of China).
5. Mechanical and Electrical Description and Software Flow Chart
NuBot Team Mechanical and Electrical Description together with a Software Flow Chart can be downloaded from here.
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.
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. Team description Paper
The team description paper can be downloaded at here, with the main contribution of a newly designed three-wheel robot.
2. 5 Papers in recent 5 years
[1] Dai, W., Yu, Q., Xiao, J., & Zheng, Z., Communication-less Cooperation between Soccer Robots. In 2016 RoboCup Symposium, Leipzig, Germany. [PDF]
[2] Xiong, D., Xiao, J., Lu, H., et al, The design of an intelligent soccer-playing robot, Industrial Robot: An International Journal, 43(1): 91-102, 2016. [PDF]
[3] Yao, W., Dai, W., Xiao, J., Lu, H., & Zheng, Z. (2015). A Simulation System Based on ROS and Gazebo for RoboCup Middle Size League, IEEE Conference on Robotics and Biomimetics, Zhuhai, China. [PDF]
[4] Lu, H., Yu, Q., Xiong, D., Xiao, J., & Zheng, Z. (2015). Object Motion Estimation Based on Hybrid Vision for Soccer Robots in 3D Space. In RoboCup 2014: Robot World Cup XVIII (pp. 454-465). Springer International Publishing. [PDF]
[5] Lu, H., Li, X., Zhang, H., Hu, M., & Zheng, Z. Robust and Real-time Self-localization Based on Omnidirectional Vision for Soccer Robots. Advanced Robotics, 27(10): 799-811, 2013. [PDF]
3. Results and awards in recent 3 years
2016
2015
