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13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018

作者： Yang, Yu Yang, Guilin Tian, Yingzhong Zheng, Tianjiang Li, Long Wang, Zhenhua Ningbo Institute of Materials Technology and Engineering CAS Ningbo315201 China Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology China School of Mechatronic Engineering and Automation Shanghai University Shanghai China Jiangsu Provincial Key Laboratory of Advanced Robotics Collaborative Innovation Center of Suzhou Nano Science and Technology Soochow University Suzhou215123 China

ISBN: (纸本)9781538637579

Lidars are commonly employed in mobile robot SLAM applications due to their high stability and high measuring accuracy. For a conventional 2D Lidar, only the planar points can be detected in once scan, which limits the robustness of SLAM algorithms. Omni-directional mobile robots with powered caster wheels have 3-DOF planar motion capabilities so that they are widely deployed in narrowly constrained environment. This paper presents a novel design of a 2.5D Lidar device, in which a 2D Lidar is mounted onto a 1-DOF liner stage that moves along the vertical direction. As a result, the 2.5D Lidar device can also perform vertical scanning within the motion range of the liner stage. Consequently, a robust SLAM algorithm based on the 2.5D Lidar device is proposed for the omni-directional mobile robot, where a frame-to-frame scan matching using ICP algorithm is employed to improve the robustness and accuracy of the scan matching. As the 2.5D points cloud is actually located in a belt-shaped space, the map can be finally constructed in a 2D mode to reduce the computational complexity. In addition, when an incorrect matching occurs, the odometry information of the mobile robot will be employed to further improve the robustness and accuracy of the scan matching algorithm. The effectiveness of the proposed approach is validated through computer simulations. © 2018 IEEE.

关键词： Optical radar

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A Novel Obstacle Collision Avoidance Strategy for Redundant Manipulator using Swivel Motion Control

A Novel Obstacle Collision Avoidance Strategy for Redundant ...

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IEEE International Conference on robotics and Biomimetics

作者： Kunlin Guo Yiming Jiang Xinyu Wu Chenguang Yang College of Automation Science and Engineering South China University of Technology Guangzhou China College of Electrical and Information Engineering Hunan University Changsha China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Bristol Robotics Laboratory University of the West of England Bristol UK

The research of humanoid 7-DoF redundant robotic manipulator has attracted increasing attention, due to its importance of using the redundancy to accomplish sub-tasks. In this paper, a novel obstacle collision avoidance strategy is proposed for the redundant manipulator. At first, a controller of swivel angle defined by a plane consists of the robot's shoulder, elbow and wrist joints is designed. Then, a null space based controller is developed to avoid a moving obstacle by controlling the swivel angle's motion. The designed swivel motion controller is not only to guarantee the end-effector tacking the desired trajectory precisely but also to accomplish obstacle avoidance task in the sub-space with the virtual repulsive force pushing from the obstacle to the swivel joints. The feasibility of the proposed control strategy is proved by simulation experiments based on a 7-DoF redundant robot.

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Indirect Control and Design of Insect-Like Flapping-Wing Micro Aerial Vehicle 3

Indirect Control and Design of Insect-Like Flapping-Wing Mic...

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2017 IEEE 第3届信息技术与机电一体化工程国际学术会议(ITOEC 2017)

作者： Dong weizhong Wang Zhi Dong Shenyang institute of Shenyang Institute of Automation State Key Laboratory of Robotics University of Chinese Academy of Science Department of Advanced Robotics Chiba Institute of Technology University of Chinese Academy of Science Shenyang Institute of AutomationState Key Laboratory of Robotics

Considering the Insect-like flapping-wing micro aerial vehicle,this paper has analyzed the composite of quasisteady *** process has associated with the affection due to addition quality

ISBN: (纸本)9781509053643;9781509053636

Considering the Insect-like flapping-wing micro aerial vehicle,this paper has analyzed the composite of quasisteady *** process has associated with the affection due to addition quality

关键词： Force Aerodynamics Uncertainty Automotive components Aircraft Vehicle dynamics Atmospheric modeling

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Flying Cyborg: A New Approach for the Study of Coleoptera's Flight Pitching

Flying Cyborg: A New Approach for the Study of Coleoptera's ...

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IEEE International Conference on Cyborg and Bionic Systems (CBS)

作者： Yao Li Ying Hu Shinjiro Umezu Hirotaka Sato School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen PR China Laboratory of Minimally Invasive Surgical Robotics and System Shenzhen Insititutes of Advanced Technology Chinese Academy of Sciences Shenzhen PR China Waseda University Tokyo Japan School of Mechanical & Aerospace Engineering Nanyang Technological University Singapore

ISBN: (数字)9781728150734

ISBN: (纸本)9781728150741

The study of flight orientation has gained more and more attention. In this study, we demonstrated a cyborg beetle for measuring body orientations in free flight, which contained a living insect platform and a miniature backpack with micro battery. While flying in a large flight chamber, the flight status of cyborg beetle could be recorded remotely. Thereafter, the effect of pitching on flight control was analyzed. According to the recorded flight data, a strong linear relationship was revealed between the pitch angles and forward accelerations, which was quantified by the Pearson's correlation coefficients and the fitting of mean forward accelerations under each pitch angle. We believe the coupling of pitch angle and forward acceleration is generated by tilted net aerodynamic force and flight air drag. The achievement of the orientation analysis would inspire a new approach to control system design of flying cyborgs and flapping-wing micro air vehicles (MAVs).

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Auto-LEE: A novel autonomous lower extremity exoskeleton for walking assistance

Auto-LEE: A novel autonomous lower extremity exoskeleton for...

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2018 IEEE International Conference on Information and automation, ICIA 2018

作者： He, Yong Wang, Chao Li, Nan Fu, Ruiqing Wu, Xinyu Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9781538680698

Wearable exoskeletons have been proven to be efficacious in aiding walking for individuals suffering from lower limb mobility disorder. However, the application of most existing devices is limited to inconvenience of usage, e.g., complicated training and unnatural gait. This paper presents a novel autonomous lower extremity exoskeleton, Auto-LEE, for the purpose of improving the practicality of walking assistive devices as well as simplifying their application process. The developed exoskeleton consists of two robotic legs, and each of them has 5 active degrees-of-freedom (DOFs) to independently control the rotations of hip, knee and ankle joints in the sagittal and coronal planes, which enables the device to possess self-balancing ability and flexible gait. The modular design concept is introduced into the structure and hardware development of Auto-LEE, making it more convenient to be assembled and maintained. In order to validate the self-balancing walking ability, virtual prototype simulation and preliminary experiment on flat terrain are implemented. © 2018 IEEE.

关键词： Exoskeleton (robotics)

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Micro Channel for Analyzing Mechanical Adaption of Cancer Cell

Micro Channel for Analyzing Mechanical Adaption of Cancer Ce...

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IEEE International Conference on Cyborg and Bionic Systems (CBS)

作者： Pengyun Li Xiaoming Liu Xiaoqing Tang Masaru Kojima Jian Huang Qiang Huang Tatsuo Arai Beijing Advanced Innovation Center for Intelligent Robots and Systems and the Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China Osaka University 1-3 Machikaneyama Toyonaka Osaka Japan Key Laboratory of Ministry of Education for Image Processing and Intelligent Control the School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9781728150734

ISBN: (纸本)9781728150741

It was reported that cancer cells could biologically respond and adapt to the confined environment during migration in extracellular matrix (ECM). But it is not clearly studied that how cancer cells respond and adapt to confined environment in mechanical way. Thus, in this study, we designed and fabricated a kind of one-layer micro channel to mimic confined environment for analyzing mechanical adaption of cell. This micro channel could apply sequential mechanical stresses on a number of cells with high throughput, and the time of cells passing through five rows of micro channels were used to evaluate their adaptability to the sequential and confined space. In experiments, each cell suffered 20 times of mechanical stresses after passing through 20 squeezing channels arranged in 5 rows. We observed the sequential squeezing processes under microscope and investigated the passing time using a high-speed camera. The preliminary results indicated that cancer cells could pass through and adapt to the confined environment faster than normal cells.

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Parallel Driving in CPSS:A Unified Approach for Transport automation and Vehicle Intelligence

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IEEE/CAA Journal of Automatica Sinica 2017年第4期4卷 577-587页

作者： Fei-Yue Wang Nan-Ning Zheng Dongpu Cao Clara Marina Martinez Li Li Teng Liu IEEE State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Advanced Vehicle Engineering Center Cranfield University Department of Automation Tsinghua University State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Qingdao Huituo Intelligent Machine Company

The emerging development of connected and automated vehicles imposes a significant challenge on current vehicle control and transportation systems. This paper proposes a novel unified approach, Parallel Driving, a cloud-based cyberphysical-social systems(CPSS) framework aiming at synergizing connected automated driving. This study first introduces the CPSS and ACP-based intelligent machine systems. Then the parallel driving is proposed in the cyber-physical-social space,considering interactions among vehicles, human drivers, and information. Within the framework, parallel testing, parallel learning and parallel reinforcement learning are developed and concisely reviewed. Development on intelligent horizon(iHorizon)and its applications are also presented towards parallel *** proposed parallel driving offers an ample solution for achieving a smooth, safe and efficient cooperation among connected automated vehicles with different levels of automation in future road transportation systems.

关键词： ACP theory connected automated driving cyber-physical-social systems(CPSS) iHorizon parallel driving parallel horizon parallel learning parallel reinforcement learning parallel testing

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CholecTriplet2021: A benchmark challenge for surgical action triplet recognition

arXiv

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arXiv 2022年

作者： Nwoye, Chinedu Innocent Alapatt, Deepak Yu, Tong Vardazaryan, Armine Xia, Fangfang Zhao, Zixuan Xia, Tong Jia, Fucang Yang, Yuxuan Wang, Hao Yu, Derong Zheng, Guoyan Duan, Xiaotian Getty, Neil Sanchez-Matilla, Ricardo Robu, Maria Zhang, Li Chen, Huabin Wang, Jiacheng Wang, Liansheng Zhang, Bokai Gerats, Beerend Raviteja, Sista Sathish, Rachana Tao, Rong Kondo, Satoshi Pang, Winnie Ren, Hongliang Abbing, Julian Ronald Sarhan, Mohammad Hasan Bodenstedt, Sebastian Bhasker, Nithya Oliveira, Bruno Torres, Helena R. Ling, Li Gaida, Finn Czempiel, Tobias Vilaça, João L. Morais, Pedro Fonseca, Jaime Egging, Ruby Mae Wijma, Inge Nicole Qian, Chen Bian, Guibin Li, Zhen Balasubramanian, Velmurugan Sheet, Debdoot Luengo, Imanol Zhu, Yuanbo Ding, Shuai Aschenbrenner, Jakob-Anton van der Kar, Nicolas Elini Xu, Mengya Islam, Mobarakol Seenivasan, Lalithkumar Jenke, Alexander Stoyanov, Danail Mutter, Didier Mascagni, Pietro Seeliger, Barbara Gonzalez, Cristians Padoy, Nicolas ICube University of Strasbourg CNRS France IHU Strasbourg France Department of Computer Science University of Chicago United States Lab for Medical Imaging and Digital Surgery Shenzhen Institute of Advanced Technology Chinese Academy of Sciences China School of Management Hefei University of Technology Hefei China Institue of Medical Robotics Shanghai Jiao Tong University Shanghai China Argonne National Laboratory 9700 S Cass Ave LemontIL60439 United States Digital Surgery A Medtronic Company London United Kingdom Institute of Automation Chinese Academy of Sciences China Department of Computer Science School of Informatics Xiamen University Xiamen China Johnson & Johnson Meander Medical Centre Netherlands Indian Institute of Technology Kharagpur India Muroran Institute of Technology Japan Department of Biomedical Engineering National University of Singapore Singapore Department for Translational Surgical Oncology National Center for Tumor Diseases Partner Site Dresden Germany 2Ai School of Technology IPCA Barcelos Portugal School of Medicine University of Minho Braga Portugal Algoritimi Center School of Engineering University of Minho Guimeraes Portugal Technical University of Munich Germany Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong Wellcome EPSRC Center for Interventional and Surgical Science University College London United Kingdom Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy University Hospital of Strasbourg France

Context-aware decision support in the operating room can foster surgical safety and efficiency by leveraging real-time feedback from surgical workflow analysis. Most existing works recognize surgical activities at a coarse-grained level, such as phases, steps or events, leaving out fine-grained interaction details about the surgical activity;yet those are needed for more helpful AI assistance in the operating room. Recognizing surgical actions as triplets of combination delivers comprehensive details about the activities taking place in surgical videos. This paper presents CholecTriplet2021: an endoscopic vision challenge organized at MICCAI 2021 for the recognition of surgical action triplets in laparoscopic videos. The challenge granted private access to the large-scale CholecT50 dataset, which is annotated with action triplet information. In this paper, we present the challenge setup and assessment of the state-of-the-art deep learning methods proposed by the participants during the challenge. A total of 4 baseline methods from the challenge organizers and 19 new deep learning algorithms by competing teams are presented to recognize surgical action triplets directly from surgical videos, achieving mean average precision (mAP) ranging from 4.2% to 38.1%. This study also analyzes the significance of the results obtained by the presented approaches, performs a thorough methodological comparison between them, in-depth result analysis, and proposes a novel ensemble method for enhanced recognition. Our analysis shows that surgical workflow analysis is not yet solved, and also highlights interesting directions for future research on fine-grained surgical activity recognition which is of utmost importance for the development of AI in surgery. © 2022, CC BY-NC-SA.

关键词： Deep learning

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3D Pose Estimation for Robotic Grasping Using Deep Convolution Neural Network

3D Pose Estimation for Robotic Grasping Using Deep Convoluti...

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IEEE International Conference on robotics and Biomimetics

作者： Yao Wang Ying Xu Xiaohui Zhang Zhen Sun Yafang Zhang Guoli Song Junchen Wang School of Mechanical Engineering and Automation Beihang University Beijing China State Key Laboratory of Robotics Chinese Academy of Sciences Shenyang China Beijing Advanced Innovation Center for Biomedical Engineering Beihang University Beijing China

ISBN: (纸本)9781728103785;9781728103778

With the progress of artificial intelligence, robots begin to enter family service. Autonomous object grasping in a cluttered scene is the most frequent operation of a service robot in daily life while it is still a challenging problem in the field of robotics. In this paper, we develop a robot system using a deep convolution neural network for 3D object grasping. The system is composed by a color camera, and a robot arm with a gripper. The color camera provides robotic vision about surrounding environments; the deep neural network performs an end-to-end mapping from vision images to the 3D poses of the object of interest; the robot arm with the gripper is then driven to grasp the object. In addition, we also present an automatic data labeling method for the training of the convolution neural network. Preliminary experiments were performed to evaluate our robot system and the results have confirmed its effectiveness.

关键词： Conferences Robots Biomimetics

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A robust and accurate SLAM algorithm for omni-directional mobile robots based on a novel 2.5D lidar device

A robust and accurate SLAM algorithm for omni-directional mo...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Yu Yang Guilin Yang Yingzhong Tian Tianjiang Zheng Long Li Zhenhua Wang CAS Ningbo Institute of Materials Technology and Engineering Ningbo China School of Mechatronic Engineering and Automation ShangHai University Shanghai China Jiangsu Provincial Key Laboratory of Advanced Robotics & Collaborative Innovation Center of Suzhou Nano Science and Technology Soochow University Suzhou China

关键词： Laser radar Mobile robots Two dimensional displays Three-dimensional displays Simultaneous localization and mapping Wheels

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