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12th International Conference on CYBER Technology in Automation, Control, and Intelligent systems, CYBER 2022

作者： Linghan, Meng Cong, Wang Shengguo, Cui Qifeng, Zhang Baoqi, Zhai State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China Guangzhou511458 China Key Laboratory of Marine Robotics Liaoning Province Shenyang110169 China University of the Chinese Academy of Sciences Beijing100049 China Guangdong Institute of Intelligent Unmanned System Guangzhou511458 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

The problem of population ageing in today's world is becoming increasingly serious, and the capacity gap in the service industry for elderly people is increasing. Especially in the current epidemic environment, the deartificialization of the service industry is imminent. For service tasks of seniors, there is no doubt that legged robots are the best choice for service tasks due to there flexibility and agility. However, complex service tasks require a mobile robotic system that integrates functions such as localization, navigation, recognition, and grasping. To this end, we propose a mobile robotic system to accomplish some daily service work such as finding and grasping some articles for daily use and then delivering them to a proposed place. We show that the system is universally applicable and highly efficient in daily environments. Videos of the experiments can be viewed at https://***/xPeBzDf6D_k or https://***/video/BV1QZ4yli7qx. © 2022 IEEE.

关键词： HTTP

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A Novel Multi-Fingered Hand for Robotic Grasp 7

A Novel Multi-Fingered Hand for Robotic Grasp

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7th Annual International Conference on Network and Information systems for Computers, ICNISC 2021

作者： Zang, Xizhe Wang, Chao Zhang, Pu Heng, Shuai Zhao, Jie State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China Zhejiang Lab Hangzhou311121 China

ISBN: (纸本)9781665402323

As robots are gradually used in more and more scenarios, the requirements for robots to complete a variety of complex tasks are becoming higher and higher. Robotic hands, as the important tool for robot to complete the task, has attracted more and more attention. However, the robotic grasping tool usually has a single function and few degrees of freedom, which makes it difficult to adapt to more complex application scenarios. This paper presented a novel robotic hand with four fingers, which is designed based on the characteristics of human hands. We introduced the design process of the finger structure, analyzed the kinematics and statics of the designed hand, and further manufactured the prototype. To verify the function of the designed multi-fingered hand, we designed a serial of grasping experiments for different objects. The experimental results show that the designed multi-fingered hand can successfully grasp different experimental objects and meet the grasping requirements of the robot. © 2021 IEEE.

关键词： Degrees of freedom (mechanics)

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A Novel Thrust Allocation Method for Underwater Robots 12

A Novel Thrust Allocation Method for Underwater Robots

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12th International Conference on CYBER Technology in Automation, Control, and Intelligent systems, CYBER 2022

作者： Zheng, Xin-Hui Wang, Cong Yang, Xue-Jiao Tian, Qi-Yan Zhang, Qi-Feng Zhai, Bao-Qi State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China Guangzhou511458 China Key Laboratory of Marine Robotics Liaoning Province Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Guangdong Institute of Intelligent Unmanned System Guangzhou511458 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Underwater vehicles with normal thruster configuration methods are unsatisfying in position-keeping tasks because of their limited manoeuvrability. To this end, this paper proposes an underwater ve-hicle with a novel thruster configuration method and solves the thrust allocation problem by the sequential quadratic programming(SQP) algorithm. Comparisons between the performance of the proposed thruster configuration method and the most widely used config-uration method are given based on the UUVSimulator and Gazebo. Numerical simulations show that vehicle with the proposed thrust configuration method has better performance in manoeuvrability and energy consumption. © 2022 IEEE.

关键词： Energy utilization

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Passive Suspension Design and Dynamics Analysis of Manned Lunar Rover

Passive Suspension Design and Dynamics Analysis of Manned Lu...

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Mechatronics and robotics Engineering (ICMRE), International Conference on

作者： Junyang Zhang Zhen Liu Zhonghao Qin State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China Special Robot Equipment Group Harbin Institute of Technology Zhengzhou Research Institute Harbin China

ISBN: (数字)9798350394276

ISBN: (纸本)9798350394283

The lunar surface environment differs significantly from that of Earth, thus necessitating the specialized design of suspension systems for lunar rovers. Within this study, a double wishbone independent suspension system is specifically designed for a manned lunar rover, with its dynamics attributes investigated through theoretical analyses and simulations. Firstly, the structural parameters of the double wishbone suspension are designed. Secondly, the theoretical dynamics model of the suspension is established, the dynamics equations are deduced, and an exploration into the impact of diverse system parameters on the suspension’s dynamics performance is conducted. Finally, the suspension underwent multi-body dynamics analysis using ADAMS to verify compliance with specified requirements for obstacle-crossing performance.

关键词： Space vehicles Suspensions (mechanical systems) Analytical models Mechatronics Moon Mathematical models Shock absorbers

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A Trajectory Planning Framework for Experimental Module Manipulator On-Orbit Servicing

A Trajectory Planning Framework for Experimental Module Mani...

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IEEE International Conference on robotics and Biomimetics

作者： Boyu Ma Baoshi Cao Yang Liu Yuteng Xie Xiaohang Yang Wei Wang Handong Hu Xiaokai Zhou Yiming Ji Zhengpu Wang Mengfei Li Haoran Sun Wandong Sun Zongwu Xie State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China School of Resources and Environment Northeast Agricultural University Harbin China

This article proposes a novel trajectory planning framework for the Experimental Module Manipulator (EMM) on-orbit servicing (OOS). For a start, the simulation system of the EMM based on Open Inventor is developed, and the trajectory planning technical route of the EMM for OOS missions is illustrated, including two main phases: large-scale transfer and small-scale approach. Before trajectory planning, the Gilbert–Johnson–Keerthi convex bounding boxes of the CSS and the EMM are modeled. Moreover, we present a Cartesian-space collision-free planning scheme. For the different task requirements in the above two phases, two corresponding collision-free trajectory planning schemes in joint space are proposed. Finally, simulations of the EMM supporting an astronaut extra-vehicular activity verify the effectiveness of our trajectory planning framework and all of the schemes presented in this article.

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Research on Low-Force Cutting Load Characteristics for Lunar Rock Simulant

Research on Low-Force Cutting Load Characteristics for Lunar...

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2021 International Conference on Computer Graphics, Artificial Intelligence, and Data Processing, ICCAID 2021

作者： Wang, Yizhuo Li, Peng Xu, Bo Liu, Junwei Mechanical Engineering College Beihua University Jilin132022 China Mechanical Engineering College Yanshan University Qinhuangdao066004 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China

ISBN: (数字)9781510652170

ISBN: (纸本)9781510652163

In the whole lunar regolith drilling and sampling task, It is critical to make the operation of the drilling and sampling system efficient and reliable. In view of the high efficiency drilling requirements of lunar rock under low-force conditions, it is necessary to study the mechanical properties of an elemental blade and lunar rock. Firstly, a test platform is developed to test the low-force cutting load characteristics for the lunar rock simulant according to the requirements of the cutting load characteristics test function. Then, the linear cutting load and impact crushing load characteristics for the lunar rock simulant are tested and verified respectively. It is finally found that the cutting load of the lunar rock simulant can be reduced by increasing the cutting edge rake angle and side rake angle and improving the percussive frequency. This provides a certain reference for setting the operating parameters of lunar rock core drilling tools to achieve high performance drilling under low-force conditions. © 2022 SPIE.

关键词： Rocks

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Obstacle Identification Based on Deep Learning for Inspection Robot of FAST Wire Rope

Obstacle Identification Based on Deep Learning for Inspectio...

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Automation, robotics and Computer Engineering (ICARCE), International Conference on

作者： Chengxu Yang Xiangyu Sun Gangfeng Liu School of Mechatronics Engineering Harbin Institute of Technology Harbin China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

In this paper, for the requirements of image recognition and localization of the obstacles existing on the moving path in the inspection task of FAST cable inspection robot, the deep learning method is used to realize the recognition of multi-kind and multi-scale obstacles. The obstacles on FAST wire rope have not been identified before. By enhancing the data set and improving the network model, the recognition accuracy and speed are both improved, which meets the efficiency and accuracy requirements of obstacle detection on the wire rope, and provides help for the subsequent robot pace planning and overhaul tasks.

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DeepMatcher: A Deep Transformer-based Network for Robust and Accurate Local Feature Matching

arXiv

引用

arXiv 2023年

作者： Xie, Tao Dai, Kun Wang, Ke Li, Ruifeng Zhao, Lijun State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150006 China SenseTime Group Inc. Beijing100080 China

Local feature matching between images remains a challenging task, especially in the presence of significant appearance variations, e.g., extreme viewpoint changes. In this work, we propose DeepMatcher, a deep Transformer-based network built upon our investigation of local feature matching in detector-free methods. The key insight is that local feature matcher with deep layers can capture more human-intuitive and simpler-to-match features. Based on this, we propose a Slimming Transformer (SlimFormer) dedicated for DeepMatcher, which leverages vector-based attention to model relevance among all keypoints and achieves long-range context aggregation in an efficient and effective manner. A relative position encoding is applied to each SlimFormer so as to explicitly disclose relative distance information, further improving the representation of keypoints. A layer-scale strategy is also employed in each SlimFormer to enable the network to assimilate message exchange from the residual block adaptively, thus allowing it to simulate the human behaviour that humans can acquire different matching cues each time they scan an image pair. To facilitate a better adaption of the SlimFormer, we introduce a Feature Transition Module (FTM) to ensure a smooth transition in feature scopes with different receptive fields. By interleaving the self- and cross-SlimFormer multiple times, DeepMatcher can easily establish pixel-wise dense matches at coarse level. Finally, we perceive the match refinement as a combination of classification and regression problems and design Fine Matches Module to predict confidence and offset concurrently, thereby generating robust and accurate matches. Experimentally, we show that DeepMatcher significantly outperforms the state-of-the-art methods on several benchmarks, demonstrating the superior matching capability of DeepMatcher. The code is available at https://***/XT1997/DeepMatcher. © 2023, CC BY.

关键词： Behavioral research

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An Efficient and Robust Tightly Coupled Framework for Lidar-IMU Localization and Mapping

An Efficient and Robust Tightly Coupled Framework for Lidar-...

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IEEE International Conference on robotics and Biomimetics

作者： Yanwu Zhai Yili Fu Xu Li Intelligent Robot Research Center Zhejiang Laboratory Hangzhou China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

In this article, we propose a framework for tightly-coupled lidar inertial odometry, which can achieve highly accuracy in real-time ego-motion estimation and map building of the robot. The estimated motion from inertial measurement unit (IMU) preintegration de-skews point clouds. Then, an initialization method based on MAP estimation is used to align the Lidar frame with the world frame and provide reliable initial values for the system. In order to make the scan matching more accurate, we track the state of each frame, and transform the feature points to the reference frame to build a local map for matching with key frames. To ensure high performance in real-time, an efficient sliding window was used to optimize the keyframes we chose. After obtaining the optimized pose of the keyframe, we further optimize the pose of the normal frame by pose constraints. In addition, loop detection is integrated into our algorithm framework to eliminate accumulated errors, making our algorithm to obtain a globally consistent estimate. The experiment results demonstrate that our method can achieve high accuracy in a variety of indoor and outdoor environments even under fast motion conditions or with insufficient features.

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OAMatcher: An Overlapping Areas-based Network for Accurate Local Feature Matching

arXiv

引用

arXiv 2023年

作者： Dai, Kun Xie, Tao Wang, Ke Jiang, Zhiqiang Li, Ruifeng Zhao, Lijun State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150006 China SenseTime Group Inc. Beijing100080 China

Local feature matching is an essential component in many visual applications. In this work, we propose OAMatcher, a Tranformer-based detector-free method that imitates humans behavior to generate dense and accurate matches. Firstly, OAMatcher predicts overlapping areas to promote effective and clean global context aggregation, with the key insight that humans focus on the overlapping areas instead of the entire images after multiple observations when matching keypoints in image pairs. Technically, we first perform global information integration across all keypoints to imitate the humans behavior of observing the entire images at the beginning of feature matching. Then, we propose Overlapping Areas Prediction Module (OAPM) to capture the keypoints in co-visible regions and conduct feature enhancement among them to simulate that humans transit the focus regions from the entire images to overlapping regions, hence realizeing effective information exchange without the interference coming from the keypoints in non-overlapping areas. Besides, since humans tend to leverage probability to determine whether the match labels are correct or not, we propose a Match Labels Weight Strategy (MLWS) to generate the coefficients used to appraise the reliability of the ground-truth match labels, while alleviating the influence of measurement noise coming from the data. Moreover, we integrate depth-wise convolution into Tranformer encoder layers to ensure OAMatcher extracts local and global feature representation concurrently. Comprehensive experiments demonstrate that OAMatcher outperforms the state-of-the-art methods on several benchmarks, while exhibiting excellent robustness to extreme appearance variants. The source code is available at https://***/DK-HU/OAMatcher. © 2023, CC BY.

关键词： Image enhancement

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