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IEEE International Conference on robotics and Biomimetics

作者： Fei WANG Lignzhou YU Han WU Ketao Shi Faculty of Robot Science and Engineering Northeastern University Shenyang China College of Information Science and Engineering Northeastern University Shenyang China

Aiming at achieving the compliance control of lower limbs exoskeleton, a compliant control strategy basing on optimized compliance algorithm was proposed. The motion trajectory of human body was collected by using inertial sensors and electromyography sensors, and the information is taken as the reference information to the exoskeleton robot. By introducing muscle activation degree as the feedforward loop to offset the hysteresis phenomenon which is shown in the process of movement, the following movement achieved compliant. The feasibility of this control method is both verified on the simulation software platform and physical prototype. The experimental results show that this control method is effective and feasible in the lower limbs exoskeleton system.

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An Acceleration Method Using CUDA based on ORB-SLAM2

An Acceleration Method Using CUDA based on ORB-SLAM2

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Zhenzhen Li Lei Zhang Chenglong Xu Fengshan Zou Jilai Song Daji Tian Faculty of Robot Science and Engineering Northeastern University Shenyang Liaoning China SIASUN Robot & Automation Co. Ltd Shenyang Liaoning China

ISBN: (数字)9781728107707

ISBN: (纸本)9781728107714

In order to solve the problem of poor real-time performance and low position accuracy when mobile robots apply the technology of simultaneous localization and mapping, this paper proposed an improved algorithm using CUDA parallel computing to do the ORB feature extraction and matching portion to reduce the running time of the algorithm based on open source ORB - SLAM2 visual SLAM algorithm. After that.,testing the algorithm with public stereo datasets by doing some comparative experiments using the laptop and camera. the experiment result shows that the proposed method by this paper can greatly reduce the time of extracting feature points, calculating feature descriptors and image matching, and also improve the accuracy of localization. Therefore, the improved algorithm can improve the operation efficiency of the algorithm and the robustness of mobile robot SLAM.

关键词： Feature extraction Graphics processing units Cameras Simultaneous localization and mapping robot vision systems Optimization

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Servomotor Modelling and Control for Medical robots

Servomotor Modelling and Control for Medical Robots

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Leqiang Shi Jilai Song Chenglong Xu Gang Li Yanchao Zhang Chong Li Faculty of Robot Science and Engineering Northeastern University Shenyang Liaoning China SIASUN Robot & Automation Co. Ltd Shenyang Liaoning China

ISBN: (数字)9781728107707

ISBN: (纸本)9781728107714

In the driving technology of brushless DC motor (BLDCM), there are two methods: vector control (sine wave control) and 120 degree square wave control (rectangular wave control). In the analysis of some applications of medical instruments by BLDCM, the vector control method makes the running noise of BLDCM small, and has good low-speed torque stability and stability, but the power loss of the vector control mode is large. In addition, the software structure is complex and the adaptability to the motor is relatively poor. In this paper, combined with the application of BLDCM in medical walking assisted robot, firstly, in Matlab/Simulink, the simulation model of the system is constructed. Then, PID parameters are obtained by modeling and analyzing the system. Through the simulation data comparison vector control and 120 degree square wave control, the speed following characteristics under two control modes prove that the superiority of using 120 degree square wave control under the premise of meeting the actual operation requirements. This paper has important guiding significance for the development of medical robot drive technology.

关键词： Mathematical model Brushless DC motors Control systems Torque Transfer functions

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Research on ORB-SLAM Autonomous Navigation Algorithm

Research on ORB-SLAM Autonomous Navigation Algorithm

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： C.L. Xu D.K. Qu C.D. Wu Z. Z. Li P. Di J. L. Song D. J. Tian Faculty of Robot Science and Engineering Northeastern University Shenyang Liaoning China SIASUN Robot & Automation Co. Ltd Shenyang Liaoning China

ISBN: (数字)9781728107707

ISBN: (纸本)9781728107714

The autonomous navigation algorithm of ORB-SLAM and its problems were studied and improved in this paper. ORB-SLAM is a fast and accurate navigation algorithm using visual image feature to calculate the position and attitude. But when there are few characteristic points in the unknown environment, ORB-SLAM algorithm falls into the situation of infinite solution, local localization error occurs, and global mapping is interrupted. Researchers have proposed an IMU/Vision fusion algorithm that neatly solves this problem. In this process, the calibration between inertial components and camera is very important, the desirable outcome of which will slow down the divergence speed of autonomous navigation system and further improve the system accuracy. In this paper, the algorithm of calibration between IMU/OE and Stereo vision exploiting the improved recursive least squares with forgetting factor (RFF) method is proposed, and then the algorithm is verified by experimental datas. The results show that the accuracy and the stability of the DR navigation system are improved, which can be applied to IMU/Vision integrated navigation system and enhance robustness of navigation system.

关键词： Simultaneous localization and mapping Dead reckoning Acceleration Autonomous robots Visualization

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Dense Stereo Matching Optimization Algorithm based on Image Segmentation and ORB Gravitational Field

Dense Stereo Matching Optimization Algorithm based on Image ...

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Chenglong Xu Chengdong Wu Daokui Qu Daji Tian Jilai Song Xiaofeng Wang Faculty of Robot Science and Engineering Northeastern University SIASUN Robot & Automation Co. Ltd Shenyang China Faculty of Robot Science and Engineering Northeastern University Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences SIASUN Robot & Automation Co. Ltd Shenyang China SIASUN Robot & Automation Co. Ltd Shenyang China

ISBN: (纸本)9781728137933

This paper reference the data field ideology from Cognitive Physics, presents a novel dense stereo matching method, in which the cost metric of robustness to texture-less and occluded regions. In order to correct the mismatching and constrain error propagation in cost aggregation, Oriented FAST and Rotated BRIEF (ORB) gravitational field is introduced to the traditional matching cost metrics on the basis of previous studies. Strong feature points can be regarded as correct depth estimation points, which can be used as the center to establish gravitational field for effective energy transmission of each pixel. Then the combined matching cost metrics are aggregated exploiting image segmentation structure. Finally, the experiments on the stereo images of datasets and ours prove that the proposed algorithm has better performance in matching accuracy and robustness.

关键词： Measurement robots Automation Robustness Smoothing methods Matched filters Image segmentation

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Game Scene Construction for Lower Limb Rehabilitation robot Based on Virtual Reality

Game Scene Construction for Lower Limb Rehabilitation Robot ...

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International Conference on Electromechanical Control Technology and Transportation (ICECTT)

作者： Yongfei Feng Di Jin Qianjun Shao Jianye Niu Luige Vladareanu Hongbo Wang Faculty of Mechanical Engineering & Mechanics Ningbo University Ningbo China Hebei Key Laboratory of Robot Sensing and Human-Robot Interaction Hebei University of Technology Tianjin China Robotics and Mechatronic Department Institute of Solid Mechanics of the Romanian Academy Bucharest Romania Parallel Robot and Mechatronic System Laboratory of Hebei Province and Key Laboratory of Advanced Forging & Stamping Technology and Science of Ministry of Education Yanshan University Qinhuangdao China

ISBN: (数字)9781728199283

ISBN: (纸本)9781728199290

At present, the number of patients with lower extremity dysfunction is increasing year by year. However, traditional rehabilitation training cannot meet the needs of patients for rehabilitation training. Rehabilitation robot is a good solution to train patients instead of the rehabilitation physician. Based on clinical practice experience, a lower limb rehabilitation training system based on virtual reality (VR) is designed, which combined the VR technology and rehabilitation evaluation program to improve the rehabilitation efficiency of patients. According to the functional requirements of the lower limb rehabilitation robot (LLR-RO), the construction of rehabilitation robot control system and sensor system is completed. Based on the Unity3D development environment, a VR scenes of space shooting is planned and created for rehabilitation training VR technology which enables patients to complete the training process while maintaining a pleasant mood. Through the software and hardware debugging, the feasibility, data transmission capability of VR-based remote rehabilitation training system and the synchronization performance of VR scenes and rehabilitation robots are verified. In the future, more virtual reality scenes will be studied to adapt to patients of different genders and ages.

关键词： Games Training Rehabilitation robotics Space vehicles Legged locomotion Aircraft Aerospace electronics

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Bimodal Face Recognition Based on Liveness Detection

Bimodal Face Recognition Based on Liveness Detection

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Wenlong Gao Kai Jia Fang Xu Fengshan Zou Jilai Song Faculty of Robot Science and Engineering Northeastern University Shenyang Liaoning China SIASUN Robot & Automation Co. Ltd. Shenyang Liaoning China

ISBN: (数字)9781728107707

ISBN: (纸本)9781728107714

In this paper, we proposed a three-dimensional face recognition method based on liveness detection. Firstly, one liveness detection method based on the three-dimensional structure of the face was proposed. According to the face feature point localization algorithm combined with the RANSAC fitting algorithm and the SVM model training prediction method, the depth information was used to judge the reality of the face, and the detection of the photo and video attacker behavior were solved. In this paper, the traditional loss function and the new central loss function were used as the supervised signals in the face recognition process. We used model fine-tuning to train two independent convolutional neural networks, and then we used the score fusion approach to fuse facial feature matching. Finally, we evaluated the Eurecom and Vap public test sets based on the way of actual application. The experimental results showed that compared with the traditional in liveness detection, our algorithm made use of the advantages of three-dimensional information to realize the judgment of face reality, and the algorithm had better accuracy in three-dimensional face recognition section.

关键词： Face Face recognition Face detection Feature extraction Image color analysis Fitting Training

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Standing Assistance Control based on Voluntary Body Movement within Safety Tolerance

Standing Assistance Control based on Voluntary Body Movement...

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International Workshop on Advanced Motion Control (AMC)

作者： Daisuke Chugo Masahiro Yokota Satoshi Muramatsu Sho Yokota Jin-Hua She Hiroshi Hashimoto Takahiro Katayama Yasuhide Mizuta Atsushi Koujina Graduate School of Science and Technology Kwansei Gakuin University Sanda Hyogo Japan School of Science and Information and Telecommunication Engineering Tokai University Hiratsuka Kanagawa Japan Faculty of Science and Engineering Toyo University Kawagoe Saitama Japan School of Engineering Tokyo University of Technology Hachioji Tokyo Japan Master Program of Innovation for Design and Engineering Advanced Institute of Industrial Technology Shinagawa Tokyo Japan Service Robot Division RT.WORKS CO. LTD Osaka Japan

ISBN: (数字)9781728131894

ISBN: (纸本)9781728131900

This paper proposes a novel standing assistance robot, which considers the posture tolerance of its user. In previous studies, conventional assistive robots did not require patients to use their own physical strength to stand, which leads to decreased strength in the elderly. Therefore, an assistive robot that allows patients to maximally use the physical strength they possess is required. To realize this objective, it is important that a robot assists patients according to their body movement and by their intentions. However, in previous studies, general assistive robots helped patients by using a fixed motion reference pathway in spite of their original intention, and as a result, these robots failed to use the physical strength of the patients. In our previous study, we investigated the posture tolerance during a standing motion. In this tolerance, patients could stand by own muscle strength with stable posture. Thus, as the next step, this paper proposes assistance force control scheme which considers the investigated posture tolerance. Our robot generated assistance force, which lead the voluntary movement with their remaining physical strength within investigated range, by combining position control and force control. A prototype assistive robot, based on the proposed idea was fabricated to help patients stand up safely using the maximum of their remaining physical strength.

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A Robust Laser-Inertial Odometry and Mapping Method for Large-Scale Highway Environments

A Robust Laser-Inertial Odometry and Mapping Method for Larg...

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2019 IEEE/RSJ International Conference on Intelligent robots and Systems (IROS)

作者： Shibo Zhao Zheng Fang HaoLai Li Sebastian Scherer Faculty of Robot Science and Engineering Northeastern University Shenyang China Robotics Institute Carnegie Mellon University Pittsburgh Pennsylvania

In this paper, we propose a novel laser-inertial odometry and mapping method to achieve real-time, low-drift and robust pose estimation in large-scale highway environments. The proposed method is mainly composed of four sequential modules, namely scan pre-processing module, dynamic object detection module, laser-inertial odometry module and laser mapping module. Scan pre-processing module uses inertial measurements to compensate the motion distortion of each laser scan. Then, the dynamic object detection module is used to detect and remove dynamic objects from each laser scan by applying CNN segmentation network. After obtaining the undistorted point cloud without moving objects, the laser-inertial odometry module uses an Error State Kalman Filter to fuse the data of laser and IMU and output the coarse pose estimation at high frequency. Finally, the laser mapping module performs a fine processing step and the “Frame-to-Model'' scan matching strategy is used to create a static global map. We compare the performance of our method with two state-of-the-art methods, LOAM and SuMa, using KITTI dataset and real highway scene dataset. Experiment results show that our method performs better than the state-of-the-art methods in real highway environments and achieves competitive accuracy on the KITTI dataset.

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A Propagation Condition Identification and Non-Line of Sight Error Mitigation Algorithm in Wireless Sensor Network

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Journal of Physics: Conference Series 2020年第1期1453卷

作者： Hao chu Siyi Lian Hao Yang Rongguang Wu Faculty of Robot Science and Engineering Northeastern University Shenyang Liaoning 110000 China

Node localization is one of key technologies in wireless sensor networks (WSN). In practice, the occlusion of obstacles often leads to large non-line-of-sight (NLOS) error. Therefore, the misidentification of LOS (line-of-sight)/NLOS conditions can seriously reduce the accuracy of localization algorithms in WSN. In this paper, we propose a novel localization algorithm based on hypothesis testing method, which combines the NLOS condition identification algorithm and the extended Kalman filter method to mitigate the NLOS error. Moreover, we introduce the false alarm rate fa to fuse the estimated values in the LOS/NLOS condition to obtain more accurate results. The simulations demonstrate that the proposed algorithm can effectively reduce the influence of NLOS error and improve the localization accuracy.

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