General

Peng Wang  

Professor

B.Sc.  M.Sc.  Ph.D.

Institute of Automation, Chinese Academy of Science


peng_wang@ia.ac.cn

+86-010-62554330

95 Zhongguancun East Road, Beijing, China, 100190

Research Areas

Robot Grasping and Manipulation

Robot Vision, Robot Learning

Neurorobotics, Brain-like Robotics

Intelligent Robot Systems.

Education

Ph.D. in Control Theory and Control Engineering (July 2010)

Robotic Theory and Application Group, State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Science (CASIA), China

M.Eng. in Control Engineering (July 2007)

School of Aeronautics, Harbin Institute of Technology (HIT), Harbin, China

B.Eng in Electrical Engineering and Automation (July 2004)

School of Automation, Harbin Engineering University (HEU), Harbin, China

Experience

2017. 10-                Professor

                                Institute of Automation, Chinese Academy of Science (CASIA), China

2018.4-2018.5       Visiting Scholar

                               University of California Berkeley (UCB), USA

2016.9-2016.10     Visiting Scholar

                               Technical University of Munich (TUM), Germany

2012.10-2017.10   Associate Professor

                             Institute of Automation, Chinese Academy of Science (CASIA), China

2010.7-2012.10    Assistant Professor

                             Institute of Automation, Chinese Academy of Science (CASIA), China

Honors & Distinctions

  • First Prize of Science and Technology of Beijing, Beijing Science and Technology Commission, 2012. 

  • Prize of Science and Technology of Beijing, Beijing Science and Technology Commission, 2015. 

  • Member of Youth Innovation Promotion Association, Chinese Academy of Sciences, 2014.

  • Top Ten Outstanding Staff, Institute of Automation, Chinese Academy of Science (CASIA), 2012.

  • Outstanding Staff, Research Center of Precision Sensing and Control, Institute of Automation, Chinese Academy of Science (CASIA), 2013.

  • Recipient of Paper Award Selected in “Top Articles from Outstanding S&T Journals of China-F5000”, Institute of Scientific and Technical Information of China.

Publications

   
Papers

  1.  Haonan Duan, Peng Wang*, Yayu Huang, Guangyun Xu, Wei Wei and Xiaofei Shen, Robotics Dexterous Grasping: The Methods Based on Point Cloud and Deep Learning, Frontiers in Neurorobotics, volume 15, 2021. doi: 10.3389/fnbot.2021.658280

  2. Wei WeiYongkang LuoFuyu LiGuangyun XuJun ZhongWanyi LiPeng Wang*, GPR: Grasp Pose Refinement Network for Cluttered Scenes, IEEE International Conference on Robotics and Automation (ICRA), 2021.arXiv:2105.08502v1 

  3. Guangyun Xu, Peng Wang*, et. al., POIS: Policy-Oriented Instance Segmentation for Ambidextrous Robot Picking, IEEE International Conference on Robotics and Automation (ICRA), 2021

  4. ​Chenlin Zhou, Daheng Li, Peng Wang*, Jia Sun, Yikun Huang, and Wanyi Li, ACR-Net: Attention Integrated and Cross-spatial Feature Fused Rotation Network for Tubular Solder Joint Detection, IEEE Transactions on Instrumentation and Measurement, 2021.  Full paper

  5. Chenlin Zhou, Peng Wang*, et. al., BV-Net : Bin-based Vector-predicted Network for Tubular Solder Joint Detection,  Measurement, Elsevier, 2021

  6. Jia Sun, Peng Wang*, Yongkang Luo, Wanyi Li. Surface Defects Detection Based on Adaptive Multi-scale Image Collection and Convolutional Neural Networks, IEEE Transactions on Instrumentation and Measurement, Volume: 68, Issue:12, 4787-4797, DECEMBER 2019. 

  7. Xuanyang Xi#, Yongkang Luo#*, Peng Wang, and Hong Qiao. Salient object detection based on an efficient end-to-end saliency regression network. Neurocomputing, 323:265–276, 2019. 

  8. Jia Sun, Peng Wang*, Yongkang Luo, Gaoming Hao, Hong Qiao. Precision Work-piece Detection and Measurement Combining Top-down and Bottom-up Saliency[J]. International Journal of Automation and Computing. vol. 15, no. 4, pp. 417-430, 2018.

  9. Wenjun Zhu, peng wang*, Rui Li ,  Xiangli Nie ,  Real-time 3D Work-piece Tracking with Mo-nocular Camera Based on Static and Dynamic Model Libraries, Assembly Automation, Vol. 37 Iss: 2, 219~229, 2017.

  10. Sun, Jia; Wang, Peng*; Qin, Zhengke; Qiao Hong,Effective self-calibration for camera parameters and hand-eye geometry based on two feature points motions,IEEE/CAA Journal of Automatica Sinica,4(2), 370–380,2017.

  11. Xu, D., Lu, J., Wang, P., Zhang, Z., & Liang, Z. Partially decoupled image-based visual servoing using different sensitive features. IEEE Transactions on Systems, Man, and Cybernetics: Systems, Volume: 47, Issue: 8, 2233 - 2243 ,Aug. 2017. 

  12. Zhengke Qin, Peng Wang*, Jia Sun, Jinyan Lu, and Hong Qiao, Precise Robotic Assembly for Large-Scale Objects Based on Automatic Guidance and Alignment,IEEE Transactions on Instrumentation and Measurement, vol. 65, no. 6, June 2016. 

  13. Wanyi LiPeng Wang, and Hong Qiao, Top-down Visual Attention Integrated Particle Filter for Robust Object TrackingSignal Processing: Image Communication, 2016 ,43 ,2841.

  14. Peng Wangand Hong Qiao, Online Appearance Model Learning and Generation for Adaptive Visual Tracking,IEEE Transactions on Circuits and Systems for Video Technology, 2011, 21(2):156-169

  15. PengWang and Hong Qiao, Adaptive probabilistic tracking with reliable particle selection,Electronics Letters, vol. 45, no. 23, pp.1160-1161,2009.

  16. Yongkang Luo, Peng Wang, et al., Sparse-Distinctive Saliency Detection,IEEE Signal Processing Letters, Volume:22,Issue: 9, 2015.

  17. Hong Qiao, Yanlin Li, Tang Tang and Peng Wang, Introducing Memory and Association Mechanism Into a Biologically Inspired Visual Model,IEEE Transactions on Cybernetics,Volume:44, Issue: 9, 1485 - 1496 , Sept. 2014

  18. Wei Liu,PengWang et. al., Part-based adaptive detection of work- pieces using Differential EvolutionSignal Processing2012, 92(2)301-307.

  19. Zhicai Ou, Peng Wang et. al., Sub-pattern bilinear model and its application in pose estimation of work-pieces,Neurocomputing2012, 83176–187.

  20. Wei Liu, Tianshi Chen, Peng Wang et. al., Pose estimation for 3D workpiece grasping in industrial environment based on evolutionary algorithm,Journal of Intelligent and Robotic Systems, (2012) 68:293–306.

  21. Dongchun Ren, Peng Wang et. al., A biologically inspired model of emotion eliciting from visual stimuli,Neurocomputing, Volume 121, Pages 328–336, 2013.

  22. Wanyi Li, Peng Wang et al., Robust object tracking guided by top-down spectral analysis visual attention,Neurocomputing, Volume 152, 25 March 2015, Pages 170–178.

  23. Wanyi Li,Peng Wang et. al., A Survey of Visual Attention Based Methods for Object Tracking.Acta Automatica Sinica,2014, 40(4): 561-576.

  24. Lu Jin-Yan, Xu De, Qin Zheng-Ke, Wang Peng, Ren Chao. An automatic alignment strategy of large diametercomponents with a multi-sensor system.Acta Automatica Sinica, 2015, 41(10): 1711-172

  25. PengWang, et al.,Salientregion detection based on Local and Global Saliency,Proceedings of IEEE International Conference on Robotics and Automation (ICRA), 1546 – 1551, 2014, Hong Kong.

  26. Peng Wang,et al.,RoboticAssembly System Guided by Multiple Visionand Laser Sensors for Large Scale Components,Proceedings of IEEE International Conference onRobotics and Biomimetics, 2015

  27. Peng Wang and Hong Qiao, 2010, Adaptive probabilistic tracking with multiple cues integration for a mobile robot,Proceedings of IEEE International Conference of Control and Automation, June 2010, pp. 713-718.

  28. Peng Wanget al., Adaptive Visual Tracking with feature selection for mobile robot,Proceedings of IEEE CYBER2014, HongKong.

  29. Peng Wang et. al., Object Tracking with Serious Occlusion Based on Occluder Modeling,Proceedings of IEEE International Conference on Mechatronics and Automation, pp. 1960-1965, 2012

  30. Jing Tao, Peng Wang et. al., Facility Layouts Based on Intelligent Optimization Approaches,Proceedings of ICIST, 2012.

  31. Wanyi Li, Peng Wang et. al., Double least squares pursuit for sparse decomposition,Proceedings of the 7th International Conference on Intelligent Information Processing,2012.

  32. Jiuqi Han and Peng Wang et.al., Tuning of PID Controller Based-on Fruit Fly Optimization Algorithm,Proceedings of IEEE International Conference on Mechatronics and Automation, 2012.

  33. Wenjun Zhu, Peng Wang*, Fudong Li, Hong Qiao,Real-time 3D Model-based Tracking of Work-piece with Monocular Camera,Proceedings of IEEE/SICE International Symposium on System Integration, Nagoya, Japan,2015

  34. Jiwu Dong, Jianhua Su, Hong Qiao and Peng Wang, Optimal Fixture Design in the Large Plates of Optical Glass Assembly,Proceedings of IEEE International Conference on Mechatronics and Automation, 2012.

  35. Wei Liu, Jianhua Su, Suiwu Zheng, and Peng Wang, Pose Estimation for 3D Work Piece Using Differential Evolution Algorithm,Applied Mechanics and Materials(Volumes 182 - 183), 1708-1712 ,2012. (EI/ISTP)

  36. Wanyi Li, Peng Wang et. al., Top-down Spatiotemporal Saliency Detection using Spectral Filtering,Proceedings of The 5th International Conference on Digital Image Processing(ICDIP 2013) . (EI/ISTP)

  37. Jing Tao, Peng Wang, et. al., Facility Layouts Based on Differential Evolution Algorithm,Proceedings of IEEE ROBIO,2013

  38. Zhengke Qin, Wenjun Zhu, Peng Wang and Hong Qiao, Workpiece Localization with Shadow Detection and Removing,Proceedings ofIEEE ROBIO,2013

  39. Wenjun Zhu, Qinzheng Ke, Peng Wang and Hong Qiao, Model-based Work-piece Localization with Salient Feature Selection,Proceedings ofIEEE ROBIO,2013

  40. Wanyi Li, Peng Wang, Visual Tracking Via Saliency Weighted Sparse Coding Appearance Model,Proceedings of ICPR,2014.

  41. Jinyan Lu, De Xu , Peng Wang, A Kinematics Analysis for a 5-DOF Manipulator,Proceedings of 2014 CCDC.

  42. Zhengke Qin, Peng Wang, et al., Polygon Detection and Localization Based on Link-line Model,Proceedings of WCICA, 2014

  43. Jia Sun, Peng Wang, et al., Overview of Camera Calibration for Computer Vision,Proceedings of WCICA, 2014

  44. Zhipeng Tang, Peng Wang, et al., Assembly Sequence Planning based on Graduated NonConvexity and Concavity Procedure,Proceedings of WCICA, 2014

  45. Jianhua Su, Peng Wang, et al., Caging Convex Polyhedral Objects with Four Fingers,Proceedings of IEEE CYBER2014, HongKong.

  46. Xinping Bu, hu su, Wei Zou, Peng Wang,Curvature Continuous Path SmoothingBased on Cubic Bezier Curves for Car-Like Vehicles,Proceedings of IEEE International Conference onRobotics and Biomimetics, 2015.

  47. Wanyi Li, Peng Wang, Hong Qiao,Object Discovery on RGB-D Data via Salient Object Proposals,Chinese Automation Congress, 2015


Grants & Projects

  1. 2035 Interdisciplinary Research Project, Neuromorphic Dexterous Robot  (PI) (1,4650,000 RMB, 2020–2022)

  2. National Natural Science Foundation of China (NSFC Grant No. 91748131):  The Perception of Dynamic Unstructured Environment and Autonomous Manipulation of Robot based on Attention-Memory-Learning Model  (PI) (630,000 RMB, 2018–2020)

  3. National Natural Science Foundation of China (NSFC Grant No. 61379097): Vision Detection and Localization for Optical-Mechanical Components (PI) (770,000 RMB, 2014–2017)

  4. National Natural Science Foundation of China (NSFC Grant No. 61100098): Vision Tracking with Visual Attention (PI) (230,000 RMB, 2012–2014)

  5. Research/Training Funding for Members of Youth Innovation Promotion Association sponsored by Chinese Academy of Sciences (PI) (400,000 RMB, 2015–2018)

  6. National Key S&T Special Projects: Modelling and Simulation for Large-scale scientific facility (PI) (900,000 RMB, 2014–2015)

  7. National Key S&T Special Projects: Modelling and Simulation for Large-scale scientific facility (PI) (500,000 RMB, 2013–2014)

  8. Robotic System for the Grasping and Installation of Large-Scale Objects (PI) (470,000 RMB, 2015–2016)

  9. Evaluation for Installation Robotic System (PI) (420,000 RMB, 2015–2016)

  10. Robotic Automatic Assembly System (PI) (490,000 RMB, 2013–2014)

  11. Control system for Production Process (PI) (450,000 RMB, 2010–2011)

  12. Vision Detection and Localization for Large-Scale Objects (PI) (180,000 RMB, 2010–2011)

  13. Theoretical model for Integrated Installation (PI) (100,000 RMB, 2011–2012)