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22nd IEEE International Conference on E-Health Networking, Application and Services, HEALTHCOM 2020

作者： Liu, Xiang Wu, Hancheng Fang, Senlin Yi, Zhengkun Wu, Xinyu CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen518055 China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Shenzhen Key Laboratory of Smart Sensing and Intelligent Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518055 China

ISBN: (纸本)9781728162676

In this paper, we propose a novel method for multimodal material classification based on ensemble learning and optimized features. The proposed method consists of three key steps. Firstly, we extract a set of features for each modality. Compared to existing methods, the extracted features are relatively simple but more effective when they are incorporated into the classifiers. Then, the feature selection algorithms, including Multi-Cluster Feature Selection (MCFS) and Laplacian Score (LS) are employed to reduce the feature dimension due to the curse of dimensionality. Finally, an ensemble learning method is proposed to integrate the merits of different feature selection methods. The effectiveness of the proposed method is demonstrated on the LMT-108 surface material dataset which includes multiple modalities such as sound, acceleration, and image. The experimental results have shown that our approach performs better than the competing methods. © 2021 IEEE.

关键词： Learning systems

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Learning Rat-Like Behavioral Interaction Using a Small-Scale Robotic Rat 12

Learning Rat-Like Behavioral Interaction Using a Small-Scale...

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

作者： Gao, Zihang Jia, Guanglu Xie, Hongzhao Guo, Xiaowen Fukuda, Toshio Shi, Qing Beijing Institute of Technology Ministry of Education Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Key Laboratory of Biomimetic Robots and Systems Beijing100081 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

In the existing robot-rat interaction, robots usually exert influence as stimuli to observe the response of target rats. However, the above single-stimulation model from robot to rat lacks a two-way communication. Therefore, we proposed a method to learn the rat-like behavioral interaction. First, we constructed two behavior patterns in the interaction process between the two rats: the individual pattern and the interaction pattern. We divided the roles of the two rats into active stimulator and passive receiver. The stimulator executes the individual pattern, and the receiver switches between the two patterns. Which pattern the receiver executes depends on the probability of interaction. Secondly, we proposed a hypothesis concerning the behavioral interaction between two rats and controlled the interaction process between two robots. Information entropy was used to measure the similarity between two robots and two rats. The results proved that the probability of interaction between rats depends on the distance of centroid and average relative velocity, and we obtained the optimal solution to express the relationship between them. In the future, the improvement of robots' interaction ability with rats will highly benefit from this study. © 2022 IEEE.

关键词： Rats

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A blocking plate manipulation robot system based on image recognition 20

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20th CISM-IFToMM Symposium on Theory and Practice of Robots and Manipulators, ROMANSY 2014

作者： Wang, Yonggui Duan, Xingguang Syed, Amjad Ali Li, Meng Kong, Xiangzhan Li, Chang Yang, Yang Chen, Ningning Intelligent Robotics Institute Key Laboratory of Biomimetic Robots and Systems Ministry of Education School of Mechatronical Engineering Beijing Institute of Technology 5 Nandajie Zhongguancun Haidian Beijing100081 China

ISBN: (纸本)9783319070575

Since the intricate and dangerous working environment of steam generator, it’s risky for staffs to complete fastening bolts of blocking plate. This paper introduces the blocking plate manipulation robot system based on image recognition. The mechanical design was proposed gradually to satisfy the requirement of compact structure, light weight and quick installation. Then the control system is displayed to guarantee precise control and safe operation. In addition, the center coordination values of the bolt based on the image recognition are extracted to guide the robot to fasten the bolts. Finally the experiment validates the effectiveness of the image recognition. © Springer International Publishing Switzerland 2014.

关键词： Image recognition

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Action recognition through fusion of sEMG and skeletal data in feature level

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Journal of Ambient Intelligence and Humanized Computing 2022年第9期13卷 4125-4134页

作者： Wang, Xinming Ding, Weili Bian, Shuangshuang Liu, Honghai Department of Automation Institute of Electrical Engineering Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province Yanshan University 438 West of Hebei Avenue Haigang District Qinhuangdao066004 China School of Mechanical Engineering and Automation State Key Laboratory of Robotics and Systems Harbin Institute of Technology Shenzhen Nanshan District Shenzhen518055 China

Human action can be recognized through a unimodal way. However, the information obtained from a single mode is limited due to the fact that a single mode contains only one type of physical attribute. Therefore, it is motivational to improve the accuracy of actions through fusion of two different complementary modality, which are the surface electromyography (sEMG) and the skeletal data. In this paper, we propose a general framework of fusion of sEMG signals and skeletal data. Firstly, vector of locally aggregated descriptor (VLAD) was extracted from sEMG sequences and skeletal sequences, respectively. Secondly, features obtained from sEMG and skeletal data are mapped through different weighted kernels using multiple kernel learning. Finally, the classification results are obtained through the model of multiple kernel learning. A dataset of 18 types of human actions is collected via KinectV2 and Thalmic Myo armband to verify our ideas. The experimental results show that the accuracy of human action recognition are improved by combining skeletal data with sEMG signals. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Musculoskeletal system

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Crawling Gait Enables Stable Quadrupedal Locomotion in A Bioinspired Robotic Rat

Crawling Gait Enables Stable Quadrupedal Locomotion in A Bio...

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2024 IEEE International Conference on Real-Time Computing and robotics, RCAR 2024

作者： Wang, Ruochao Quan, Xiaolong Xiao, Hang Du, Rongjie Qin, Boyang Shi, Qing Beijing Institute of Technology Intelligent Robotics Institute School of Mechatronical Engineering Beijing China Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Ministry of Education Beijing China

ISBN: (纸本)9798350372601

Constrained by the performance of actuators and controllers, achieving stable walking in small-scale quadruped robots has been more challenging compared to larger ones. Rats, in their natural habitat, can achieve stable walking even in extreme environments like narrow spaces by utilizing crawling motion to lower their center of mass. Inspired by this, we conducted a comparative study of the walking stability between crawling and trot gaits on a ratinspired robot named SQuRo. Initially, we collected motion data for both crawling and trot gaits of SQuRo in a simulated environment. Subsequently, we analyzed the dynamic stability of the robot using Poincaré maps. The results indicate that SQuRo's phase trajectories converged into closed loops with periodicity under both gaits, demonstrating the presence of limit cycles. Moreover, fixed points were observed in the Poincaré maps for both gaits, suggesting the dynamic stability of quadrupedal locomotion. Compared to the trot gait, the convergence loops of the crawling gait phase trajectories were smaller, indicating more stable locomotion. We tested the performance of SQuRo's crawling gait in challenging outdoor environments, where SQuRo demonstrated stable walking consistently. This work provides a new approach for achieving stable walking in small-scale quadruped robots and can be readily applied to controller design across different sizes of legged robots. © 2024 IEEE.

关键词： Rats

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Kinematics analysis and trajectory planning of a multiarm medical robot assisted maxillofacial surgery

Kinematics analysis and trajectory planning of a multiarm me...

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6th International Conference on Complex Medical Engineering, CME 2012

作者： Chen, Chao Duan, Xing-Guang Wang, Xing-Tao Zhu, Xiang-Yu Li, Meng Intelligent Robotics Institute Key Laboratory of Biomimetic Robots and Systems Ministry of Education State Key Laboratory of Intelligent Control and Decision of Complex System School of Mechatronical Engineering Beijing Institute of Technology #5Zhongguancun South Street Haidian Beijing China China

ISBN: (纸本)9781467316163

As the complex anatomical structure of the maxillofacial region, the surgery in this area is high risk and difficult to implement. Then, a multi-arm medical robot assisted maxillofacial surgery using optical navigation was proposed in this paper, which can improve surgical precision and make the doctors away from the heavy manual work. In this paper, the medical robot system and mechanical structure of the robot were introduced. Forward kinematics and inverse kinematics were analysed. Then trajectory planning using quintic polynomial interpolation for smoothly motion was adopted, and rectilinear motion in Cartesian space was adopted. The kinematics was validated and the workspace of the robot was calculated by simulations. Finally, the robot model was established and an experiment was carried out which proved the robot run smoothly and positioned accurately. © 2012 IEEE.

关键词： Inverse kinematics

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Walking Control for a Self-Balancing Exoskeleton on Flat Ground

Walking Control for a Self-Balancing Exoskeleton on Flat Gro...

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Li, Jinke Tian, Dingkui Li, Feng Sun, Jianquan Yin, Meng Wu, Xinyu University of Chinese Academy of Sciences Shenzhen College of Advanced Technology Shenzhen518055 China Siat Cuhk Joint Laboratory of Robotics and Intelligent Systems China Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen518055 China

ISBN: (纸本)9798350327182

Designed to provide rehabilitation or the assistance of walking for individuals who are with lower limb muscle injuries or spinal during their activities, self-balancing lower limb exoskeletons have been developed. This paper introduces an innovative controller for a fully actuated exoskeleton that ensures stable walking for wearers without the need for external devices. The exoskeleton robot is represented as a center of mass model, and based on this representation, the trajectory generation and controller are discussed, aiming to improve locomotion stability. To assess the stability and dynamic performance, a stable walking experiment with the exoskeleton was conducted, involving a male subject. © 2023 IEEE.

关键词： Exoskeleton (robotics)

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Flapping-Wing Robot Achieves Multi-Domain Locomotion Using Transformable Wheel Mechanism

Flapping-Wing Robot Achieves Multi-Domain Locomotion Using T...

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2024 IEEE International Conference on robotics and biomimetics, ROBIO 2024

作者： Chai, Xiangxiao Wang, Shihua Pan, Erzhen Xu, Wenfu Shenzhen518055 China Key University Laboratory of Mechanism & Machine Theory and Intelligent Unmanned Systems of Guangdong Shenzhen518055 China Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150001 China

ISBN: (纸本)9781665481090

The difficulty of moving from aquatic to aerial environment is one of the major challenges limiting the development of trans-medium multi-domain locomotion vehicles. In this paper, the concept of the transformable wheel, a feature commonly found in autonomous land vehicles (AL V s), is introduced into the design. Additionally, a flapping-wing robot equipped with multi-domain locomotion capability, which can not only realize aerial flight and surface navigation on water, but also ascend from water to land for subsequent takeoff is presented. The paper first introduces the system design of the robot and proposes the corresponding multi-domain locomotion strategy. Subsequently, the design of the transformable wheel mechanism is described in detail and the force analysis for the water-exit is conducted. The feasibility of the proposed strategy is experimentally validated, confirming the prototype's multi-domain locomotion performance finally. This research explores the feasibility of introducing the transformable wheel mechanism into trans-medium multi-domain vehicle platforms and provides a design example. © 2024 IEEE.

关键词： Machine design

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TactCapsNet: Tactile capsule network for object hardness recognition

TactCapsNet: Tactile capsule network for object hardness rec...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Fang, Senlin Mi, Tingting Zhou, Zhenning Ye, Chaoxiang Liu, Chengliang Wu, Hancheng Yi, Zhengkun Wu, Xinyu Shenzhen Institute of Advanced Technology CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518055 China Shenzhen Key Laboratory of Smart Sensing and Intelligent Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518055 China

ISBN: (纸本)9781665436786

Hardness is one of the most essential tactile clues for robots to recognize objects. However, methods for robots to recognize hardness are limited. In this paper, based on the Capsule Network (CapsNet), we propose a novel tactile capsule network (TactCapsNet) for object hardness recognition. Specifically, we collect a tactile dataset on the silicone samples with three different shapes, and the silicone samples of each shape have thirteen hardness levels ranging from 0A (Shore A scale) to 60A at 5A intervals. Furthermore, we construct the tactile image as the input of the CapsNet to make full use of the spatio-temporal information of the tactile hardness dataset. The experimental results prove that the proposed approach achieves higher accuracy and quadratic weighted kappa (QWK) than support vector machine (SVM), long short-term memory (LSTM), convolutional neural network (CNN), and CapsNet. © 2021 IEEE.

关键词： Hardness

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Powered Super Tail: A Terrain-Adaptive Wheel-legged Robotic Limb to Assist Human’s Load Carriage

Powered Super Tail: A Terrain-Adaptive Wheel-legged Robotic ...

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International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Yanzhen Xiang Xiaoyu Yan Hanqi Su Nuo Chen Shangkun Guo Jielin Wu Yuquan Leng Chenglong Fu Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems and Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China

ISBN: (纸本)9781665431545

Load carriage is a common demand in humans’ daily life. Long time load carriage often causes significant energy expenditure for the body and may even bring physical problems like muscle strain. Variations in terrains and ground conditions are usually inevitable in such scenarios, which disrupts humans’ gait and leads to even more energy expenditure. In this paper, a wheel-legged robotic limb, Powered Super Tail (PST) to assist human’s load carriage in varying terrains and ground conditions is proposed. The PST system mainly consists of a support rod transferring load to the ground and a pair of stepping triple wheel groups adaptable to different terrain conditions including ground barriers, stairs and rough roads. Driven by a pair of motors, uplifting support for the load and appropriate force assistance could be effectively provided by the support rod, and thus energy expenditure of human body could be reduced. The system’s performance on human body was tested. It is shown that the stepping triple wheel group could successfully traverse barriers of different heights and ascend stairs. The effect of the system on human body standing and walking on flat ground were respectively evaluated under three experimental conditions including 1) with the load only (LOAD, 16.42 kg); 2) with the powered PST (PST_ON, 27.30 kg); 3) with unpowered PST (PST_OFF, 27.30 kg). And the percentage of metabolic power consumption reduction was the metric for evaluation. Experiments demonstrate the following results: during standing, the metabolic power consumption under PST_ON is lowered by 5.42% compared to LOAD and 12.56% compared to PST_OFF; and during walking, the metabolic power consumption is lowered by 20.85% compared to LOAD and 36.58% compared to PST_OFF.

关键词： Legged locomotion Measurement Power demand Mechatronics Roads Machine vision Wheels

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