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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Hu, Longlong Tang, Lingqi Chen, Hao Li, Yao Li, Bing Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen518055 China Machine Theory and Intelligent Unmanned Systems of Guangdong Key University Laboratory of Mechanism Shenzhen518055 China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China

ISBN: (纸本)9781665481090

Many insects and miniature robots can traverse through narrow spaces via jumping motion;however, successful jumping and landing remains challenging in small-scale. No jumping robot within 90 g have yet demonstrated multiple jumping and perching successfully. Here, we demonstrate continuous jumping and perching of a miniature robot. The origami-inspired structure was manufactured by smart composite microstructure technology. A novel jumping mechanism was designed to load adjustable jump energy actuated by only one motor. A perching mechanism with two adhesive pads was designed to passively couple with the jumping mechanism, achieving perching on the ground and automatically detaching before the next jump. The jumping mechanism achieved adjustable jumping energy, corresponding to jumping height from 0.7 cm to 36.4 cm. The perching mechanism provided successful landing within a wide range (when velocity angle according to vertical direction =18, the velocity magnitude 3.4m/s, the body angle 30). Unlike typical jumping robots performing uncontrollable landing and free-rolling, our robot kept its body up-righted during the whole movement and avoided free-rolling after landing. The self-contained prototype had 18 g of mass, 6.5 cm of body height, and 36.4 cm of maximum jumping height. Finally, an eccentric motor was integrated to perform multiple omnidirectional jumping and perching movements;this represents significant improvement of motion ability for small-scale mobile robots. © 2024 IEEE.

关键词： Landing

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Adaptive-extremum seeking control algorithm to seek the odor source using a multi-agent system 41

Adaptive-extremum seeking control algorithm to seek the odor...

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第41届中国控制会议

作者： Meh Jabeen Qing-Hao Meng Li-Cheng Jin Sheng Jin Zhen-Yu Deng Institute of Robotics and Autonomous Systems School of Electrical and Information EngineeringTianjin University Department of Software Engineering The University of Lahore Tianjin Fire Science and Technology Research Institute of MEM

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This study aims to seek the odor source using a multi-agent *** main challenge of the odor source seeking is to search the optimal extremum in the presence of multiple local extrema in a gradient complex *** this,an adaptive-extremum seeking control(adaptive-ESC) algorithm has been *** are navigated to the vicinity of the source based on an estimated gradient using *** the proposed algorithm,both the integral gain and the amplitude of the perturbation signal are adjusted *** local convergence of the algorithm has been proved using averaging *** performance of the proposed algorithm is validated through simulations by employing a multi-agent system.

关键词： Odor source seeking Extremum seeking control Adaption approaches

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Collaborative Pushing and Grasping in Complex Scenarios via a Generator-Evaluator Network with Multiple Action Primitives 17th

Collaborative Pushing and Grasping in Complex Scenarios vi...

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17th International Conference on intelligent robotics and Applications, ICIRA 2024

作者： Zuo, Guoyu Wang, Zihao Luo, Yongkang Yu, Shuangyue Zhao, Min School of Information Science and Technology Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Computing Intelligence and Intelligent Systems Beijing100124 China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9789819607761

As robotic technologies advance, robotic arm manipulation tasks in complex environments become increasingly important. This paper presents a new collaborative pushing and grasping strategy to address two major challenges robotic arms encounter in complex environments: invisibility and tight enclosure of target objects. We propose a generator-evaluator network architecture based on multiple action primitives, incorporating hierarchical reinforcement learning and Double DQN techniques to optimize the operational efficiency of the robotic arm. By introducing a new action primitive to prioritize pushing operations around the topmost objects in space, our approach effectively reveals and locates obscured target objects. Additionally, utilizing the Spatial Correlation Test (SCT), our method explores all possible collision-free operational positions in the action space, selecting the optimal position from among them. Experimental results demonstrate that our approach achieves high efficiency and success rates in scenarios with randomly distributed objects, objects tightly enclosed by others, and invisible objects. This strategy enhances the speed and accuracy of tasks and improves the robot’s adaptability to complex environments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Robotic arms

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The Journey/DAO/TAO of Embodied Intelligence: From Large Models to Foundation Intelligence and Parallel Intelligence

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1313-1316页

作者： Tianyu Shen Jinlin Sun Shihan Kong Yutong Wang Juanjuan Li Xuan Li Fei-Yue Wang College of Information Science and Technology Beijing University of Chemical TechnologyBeijing 100029China School of Electrical and Information Engineering Jiangsu UniversityZhenjiang 212013China State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and RoboticsCollege of EngineeringPeking UniversityBeijing 100871China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Peng Cheng Laboratory Shenzhen 518000China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China IEEE

THE tremendous impact of large models represented by ChatGPT[1]-[3]makes it necessary to con-sider the practical applications of such models[4].However,for an artificial intelligence(AI)to truly evolve,it needs to possess a physical“body”to transition from the virtual world to the real world and evolve through interaction with the real *** this context,“embodied intelligence”has sparked a new wave of research and technology,leading AI beyond the digital realm into a new paradigm that can actively act and perceive in a physical environment through tangible entities such as robots and automated devices[5].

关键词： Intelligence DAO TAO

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Advancing Topic Segmentation of Broadcasted Speech with Multilingual Semantic Embeddings

arXiv

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arXiv 2024年

作者： Shukla, Sakshi Deo Denisov, Pavel Turan, Tugtekin Fraunhofer Institute for Digital Media Technology Germany Fraunhofer Institute for Intelligent Analysis and Information Systems Germany

Recent advancements in speech-based topic segmentation have highlighted the potential of pretrained speech encoders to capture semantic representations directly from speech. Traditionally, topic segmentation has relied on a pipeline approach in which transcripts of the automatic speech recognition systems are generated, followed by text-based segmentation algorithms. In this paper, we introduce an end-to-end scheme that bypasses this conventional two-step process by directly employing semantic speech encoders for segmentation. Focused on the broadcasted news domain, which poses unique challenges due to the diversity of speakers and topics within single recordings, we address the challenge of accessing topic change points efficiently in an end-to-end manner. Furthermore, we propose a new benchmark for spoken news topic segmentation by utilizing a dataset featuring approximately 1000 hours of publicly available recordings across six European languages and including an evaluation set in Hindi to test the model’s cross-domain performance in a cross-lingual, zero-shot scenario. This setup reflects real-world diversity and the need for models adapting to various linguistic settings. Our results demonstrate that while the traditional pipeline approach achieves a state-of-the-art Pk score of 0.2431 for English, our end-to-end model delivers a competitive Pk score of 0.2564. When trained multilingually, these scores further improve to 0.1988 and 0.2370, respectively. To support further research, we release our model along with data preparation scripts, facilitating open research on multilingual spoken news topic segmentation. © 2024, CC BY-NC-SA.

关键词： Semantic Segmentation

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A Novel Parameter-dependent Input Normalization-based Direct MRAC with Unknown Control Direction 63

A Novel Parameter-dependent Input Normalization-based Direct...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Gong, Yizhou Pin, Gilberto Zhang, Yanjun Wang, Yang ShanghaiTech University School of Information Science and Technology Shanghai China Digital Technology Org. of Electrolux Italia S.p.A. Italy Beijing Institute of Technology School of Automation Beijing100081 China Beijing Institute of Technology State Key Lab of Automation Intelligent Unmanned Systems Beijing100081 China

ISBN: (纸本)9798350316339

In this paper, we endow the model reference adaptive control (MRAC) with a novel parameter-dependent input normalization (PIN) to completely eliminate the conventional assumption of the high-frequency gain. Specifically, neither the sign nor the prior knowledge of the upper or lower bounds is required. To this end, we resort to an error augmentation together with a smart design of an adaptive law with a dead zone operation. Global stability in the mean square sense is established with the conventional proof concepts of the augmented error approach. In this way, no persistent excitation requirement is required. Although the system in question is assumed to be unity-relative-degree, the proposed technique can be easily extended to systems of arbitrary relative degrees. Finally, compared with the Nussbaum function-based methods in a numerical experiment, we show that transient behavior in our method is significantly improved. © 2024 IEEE.

关键词： Dead zones

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A Novel Mobile Robot Localization Method Based on Global Vision System 18th

A Novel Mobile Robot Localization Method Based on Global Vi...

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18th Chinese intelligent systems Conference, CISC 2022

作者： He, Yu Cheng, Lei Wang, Kunkun Ding, Ao School of Information Science and Engineering/School of Artificial Intelligence Wuhan University of Science and Technology Wuhan430010 China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan430010 China

ISBN: (纸本)9789811962028

Localization is the primary problem of mobile robot navigation. Most of the existing research on mobile robot localization algorithms is based on LiDAR or stereo cameras. Each of these methods requires the necessary sensors to be installed on the robot. These sensors are expensive and have high requirements for mounting locations, which has caused inconvenience to the design of the robot. In this paper, we propose a robot localization method based on a global vision system. A deep learning-based object detection algorithm is used to identify the robot’s position on the image from a third-person view monocular camera. Then we map and correct the coordinate of the detection results to obtain the world coordinate of robots. Experiments have demonstrated that our method can achieve an average localization accuracy of 0.14 m while having real-time performance. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Object detection

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Eye Movement Events Detection with KNN-GA and Prior Knowledge 2

Eye Movement Events Detection with KNN-GA and Prior Knowledg...

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2nd International Conference on Computer Engineering and Application, ICCEA 2021

作者： Zhong, Zheng Fang, Hongping Zhang, Hanyuan Wu, Shiqian Institute of Robotics and Intelligent Systems School of Information Science and Engineering Wuhan China

ISBN: (纸本)9781665426169

Aiming at the problems of difficulty in threshold adjustment and low detection accuracy and efficiency, an eye movement event detection method combining K-Nearest Neighbor and genetic algorithm (KNN-GA) and prior knowledge is proposed. Firstly, design the absolute amplitude feature of eye movement to describe the eye movement event characteristics of PSOs, and then the KNN is used to pre-detect eye movement events based on the minimum feature subset generated by genetic algorithm;After that, screening rules based on prior knowledge are ted to further adjust and optimize the pre-detection results. Experimental results show that this algorithm avoids threshold adjustment, and its execution efficiency is equivalent to simple IVT and NH, meanwhile the detection accuracy of fixation, saccade, and PSOs are increased by at least 3.4%, 4.7%, and 12.7%, respectively, and the detection performance is robust under different noise levels. © 2021 IEEE.

关键词： Genetic algorithms

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Low-light image enhancement and acceleration processing based on ZYNQ

Low-light image enhancement and acceleration processing base...

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2021 China Automation Congress, CAC 2021

作者： Chen, Zehe Wu, Shiqian Institute of Robotics and Intelligent Systems School of Information Science and Engineering Wuhan China

ISBN: (纸本)9781665426473

Most embedded vision systems are used to capture an image in low-light condition which results in an image with low visibility and quality. However, high-performance image enhancement algorithms take up lots of chip resources and are time consuming in embedded vision application scenarios with high real-time requirements. In this paper, a multi-core heterogeneous embedded vision system is designed based on ZYNQ, and it uses the optimized screen blending algorithm to complete the enhancement of low-light images. First, the inverse color coefficient is optimized to enhance the texture details of the image. Secondly, adaptive gamma correction is performed on the inverted image to maintain the trueness of the enhanced image color. Finally, through reasonable hardware and software co-design, the inverse color coefficient is calculated by hardware logic circuit to speed up the algorithm. Experimental results show that the low-light images collected and processed by this system have a certain improvement in the image quality than the original algorithm. The processing speed is nearly 5 times faster than without hardware acceleration, which meets the real-time requirements of embedded vision systems. © 2021 IEEE

关键词： Image enhancement

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Robustness and Push Recovery of Humanoid Robots Using Predictive and Whole-Body Control

Robustness and Push Recovery of Humanoid Robots Using Predic...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Shaojie Zhang Fenglei Ni Xueai Li Xu Li Yi Ji Xiangyu Shao State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China Key Laboratory of Autonomous Intelligent Unmanned Systems Harbin Institute of Technology Harbin China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

Robustness walking and recovery ability in uneven terrains and unexpected collisions are crucial for the practical application of humanoid robots. However, existing methods struggle to effectively balance stability, motion safety and walking agility. This paper proposes a hybrid control strategy combing Nonlinear Model Predictive Control (NMPC) and Whole-Body Control (WBC) to improve the robot's walking stability and reaction safety in collisions situations. The NMPC generates long-term and macroscopic movements, with capture point theory being utilized for foot placements determination under external impacts. On this foundation, the WBC regulates the robot refinedly in real-time based on task priorities and weights. Simulations verify the effectiveness of the proposed method, involving uneven terrain walking and external impacts rejection.

关键词： Legged locomotion Resistance Humanoid robots Stability analysis Robustness Real-time systems Planning Collision avoidance Motion analysis Predictive control

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