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2024 IEEE International Conference on Unmanned Systems, ICUS 2024

作者： Shao, Shiliang Shi, Xianyu Wang, Shaocong Liu, Da Liu, Yong Wang, Ting State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of the Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350384185

Planning secure and dependable paths for autonomous robot systems is crucial in uneven terrains. This research introduces an improved heuristic path-planning (IHPP) algorithm with multiple constraints. Initially, SLAM algorithm is utilized to generate a point cloud map of the uneven terrain, evaluating geometric information such as slope, roughness, and vertical obstacle height through the voxelized grid. Next, considering the robot's traversal capabilities, a non-linear relation is established between the robot's safe traversal cost and the geometric structure of the terrain to prevent hazardous behaviors like overturning on uneven terrain. Subsequently, the heuristic function of the IHPP algorithm is refined by utilizing the benefits of Chebyshev distance to handle obstacle avoidance. In addition, the cosine similarity to limit the deviation between the robot's current and target directions. This optimization aims to optimize the robot's turning behavior and minimize unnecessary turns, achieving smoother and greater path planning. Finally, experiments were conducted in four environments to validate the applicability and advantages of this algorithm in addressing safety path planning problems in uneven terrains. © 2024 IEEE.

关键词： Robot programming

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Highly Compressible and Stretchable Piezoresistive Sensor Based 3D Graphene-Melamine Composite Foam for Gait Motion Detection 16th

Highly Compressible and Stretchable Piezoresistive Sensor Ba...

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Owusu, Eric Kwame Djoulde, Aristide Jiang, Zhen Liu, Mei Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China

ISBN: (纸本)9789819964857

High-performance piezoresistive sensors that are stretchable, compressible, and ultralight have fueled significant interest in gait motion detection. However, developing a highly sensitive, low-cost sensor with ultralow detection and excellent mechanical stability for sensitive body flexion monitoring is a significant challenge. To address the aforementioned challenges, a stretchable and compressible piezoresistive pressure sensor is fabricated by embedding multilayer graphene (Gr) nanoparticles into the porosity of melamine foam (MF). The graphene melamine nanocomposite foam (GMNCF) is prepared by soaking the MF in a dissolved dispersion of Gr. The as-fabricated GMNCF piezoresistive sensors featured sensitivities ranging between, 0.11–8.21 kPa−1 in pressure ranges between 0–0.03 kPa, as well as excellent durability over a long period of time (1000 s). The device can effectively detect gait motions such as jogging, walking, running, heel striking, foot flat, and toes-off due to its strong piezoresistive sensing capabilities. Our results showcase the potential application of GMNCF, as a wearable device for monitoring human motions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Graphene

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Fusing Dynamics and Reinforcement Learning for Control Strategy: Achieving Precise Gait and High Robustness in Humanoid Robot Locomotion 23

Fusing Dynamics and Reinforcement Learning for Control Strat...

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23rd IEEE-RAS International Conference on Humanoid Robots, Humanoids 2024

作者： Zhao, Zida Huang, Haodong Sun, Shilong Li, Chiyao Xu, Wenfu Harbin Institute of Technology Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics School of Mechanical Engineering and Automation Shenzhen518055 China

ISBN: (纸本)9798350373578

Achieving precise gait planning and high robustness in locomotion control is crucial for the development and application of humanoid robots. In this paper, a novel control strategy is proposed, which combines dynamics control and reinforcement learning (RL), leveraging the precision of dynamics control and the robustness of RL. Specifically, foot placements for each step of the humanoid robot are designed, and the trajectories of the center of mass (CoM) and feet are obtained using a 3D linear inverted pendulum model (3D LIPM). Subsequently, joint angles during motion are calculated based on the trajectories of the CoM and feet using inverse kinematics equations. Finally, the obtained joint angles are trained as baseline actions using RL algorithms. To enhance control robustness, parameter domain randomization is introduced during the training process. By employing this control strategy, simulations of various single-step gaits, such as walking forward, walking to the right, and making right turns, are achieved. Additionally, trajectory tracking, locomotion tests on different terrains, and disturbance resistance are conducted. The simulation results demonstrate that the proposed control strategy enables precise gait control and exhibits strong robustness in humanoid robots. © 2024 IEEE.

关键词： Inverse kinematics

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Wearable Piezoresistive Pressure Sensor Based on Graphene and PDMS Nanocomposite Sponge for Foot Steps Detection 3

Wearable Piezoresistive Pressure Sensor Based on Graphene an...

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3rd International Conference on Computer, Control and robotics, ICCCR 2023

作者： Owusu, Eric Kwame Djoulde, Aristide Liu, Mei Zhen, Jiang School of Mechatronic Engineering and Automation Shanghai University Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai200444 China

ISBN: (纸本)9781665492126

Wearable sensors based on nanocomposite sponge are gaining popularity due to their high sensitivity, stretchability and offer new opportunities for applications ranging from finger motion detection to soft robotics. However, when designing skin-Adaptable, mountable, or non-invasive wearable devices, several features need to be taken into account, such as stretchability, flexibility, sensitivity, and biocompatibility. Herein, we present a facile, cost-effective, flexible, and stretchable piezoresistive pressure sensor based on a graphene/polydimethylsiloxane (PDMS) nanocomposite sponge (GPNCS) for finger motion detection. The maximum sensitivities were 133.95 kPa-1 for the pressure range of 1-10 N and 5.05 kPa-1 for the pressure range of 10-20 N respectively. When various pressures are applied, the pressure response of the devices are highly stable, repeatable, and reversible. Moreover, the piezoresistive pressure sensor has excellent sensing performance at various pressures ranging from 1 to 20 N and is mechanically robust enough to work under repeated load without degradation. The proposed device demonstrated an exceptional ability to monitor small and large finger motion, which has numerous applications in the range of finger motion detection, flexible insole as wearable healthcare monitoring and gait monitoring device © 2023 IEEE.

关键词： Graphene

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Potential Energy Recovery of Robotic Extractors for Low Carbon Footprint 16th

Potential Energy Recovery of Robotic Extractors for Low Carb...

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Zhang, Chenyue He, Bin Li, Guiqin Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China

ISBN: (纸本)9789819965007

Robotic excavators have long been recognized as significant contributors to the carbon footprint of the construction machinery sector due to their high energy consumption. As global construction projects continue to escalate, there is an urgent need to prioritize energy conservation and environmental protection. This is particularly crucial in the current Chinese context, where the nation is striving to achieve a "carbon peak" and "carbon neutrality" by balancing carbon emissions through removal or offsetting measures. The objective of this research is to develop and study hydraulic energy-saving technologies for robotic excavators, aiming to reduce their carbon footprint and align with carbon neutrality goals. By focusing on the boom descent potential energy recovery technology, the research seeks to harness the energy generated during boom movement and utilize it efficiently, thereby minimizing energy consumption and mitigating environmental impacts. The adoption of this innovative technology holds immense promise for reducing carbon emissions associated with robotic excavators. By recovering and utilizing the potential energy generated during boom descent, the overall energy consumption of the excavators can be significantly reduced, leading to a considerable decrease in their carbon footprint. By integrating low-carbon practices into the manufacturing and operation of construction machinery, this research strives to achieve substantial reductions in carbon emissions and foster a greener future. Through the development and implementation of carbon footprint reduction strategies, the construction machinery industry can actively contribute to China's carbon neutrality objectives and support global efforts towards mitigating climate change. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Potential energy

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Design and experiment of a novel pneumatic soft arm based on a deployable origami exoskeleton

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Frontiers of Mechanical Engineering 2023年第4期18卷 119-130页

作者： Yuwang LIU Wenping SHI Peng CHEN Yi YU Dongyang ZHANG Dongqi WANG State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China School of Mechanical Engineering Northeastern UniversityShenyang 110000China University of Chinese Academy of Sciences Beijing 100049China

Soft arms have shown great application potential because of their flexibility and compliance in unstructured ***,soft arms made from soft materials exhibit limited cargo-loading capacity,which restricts their ability to manipulate *** this research,a novel soft arm was developed by coupling a rigid origami exoskeleton with soft *** joint module of the soft arm was composed of a deployable origami exoskeleton and three soft *** motion and load performance of the soft arm of the eight-joint module was *** developed soft arm withstood at least 5 kg of load during extension,contraction,and bending motions;exhibited bistable characteristics in both fully contracted and fully extended states;and achieved a bending angle of more than 240°and a contraction ratio of more than 300%.In addition,the high extension,contraction,bending,and torsional stiffnesses of the soft arm were experimentally demonstrated.A kinematic-based trajectory planning of the soft arm was performed to evaluate its error in repetitive *** work will provide new design ideas and methods for flexible manipulation applications of soft arms.

关键词： pneumatic soft arm soft airbag deployable origami exoskeleton bistable characteristics cargoloading capacity

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Control and Planning of Rotary Wing Unmanned Aerial Vehicles Applied to High-altitude Cableway Detection

Control and Planning of Rotary Wing Unmanned Aerial Vehicles...

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2024 IEEE International Conference on Unmanned Systems, ICUS 2024

作者： Zhang, Xuan Yang, Liying Li, Siliang Huang, Zhaoxiong He, Yuqing State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences China University of Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350384185

A novel detection method is to use unmanned aerial vehicles for the detection of high-altitude passenger *** paper posed a challenging problem for detection system modeling and *** article proposed a method of detecting high-altitude passenger ropeways by connecting two unmanned aerial ***, the structural composition of the detection system was designed according to the testing ***, the dynamic models of the two drones are *** this, a geometric controller is used to ensure the exactly tracking of the planed ***, the feasibility and validity are verified in the experiment. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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A multi-objective optimization trajectory interpolation method based on fifth-degree B-spline curves

A multi-objective optimization trajectory interpolation meth...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Yang, Qiang Hu, Xiaomeng Du, Liang Bao, Sheng Yuan, Jianjun School of Mechatronic Engineering and Automation Shanghai University Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai200444 China Shanghai Robotics Institute Shanghai University Shanghai China

ISBN: (纸本)9798350325706

With the increasing use of special-purpose robots with heavy load requirements in narrow and critical environments , the operation safety and collision avoidance of such robots have become closely related, making trajectory planning an important research direction today. This paper proposes a path points interpolation method suitable for generating multi-objective optimized motion trajectories for specific tasks, thereby improving the overall performance of the robot, especially its operational manipulability. It mainly focuses on the joint space of the robot, optimizing its velocity, acceleration, position, and force. We use two evaluation functions to compare the performance of the modified B-spline method, and employ a genetic algorithm to find the best solution. Simulation and experimental demonstrations are conducted to validate the effectiveness of the trajectory optimization. The trajectory interpolation method we proposed can optimize various performance aspects of the robot while also providing a wider range of optimization options. © 2023 IEEE.

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Simulation and implementation of deep learning based expression recognition

Simulation and implementation of deep learning based express...

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2024 International Conference on Mechatronic Engineering and Artificial Intelligence, MEAI 2024

作者： Qin, Lijuan Wang, Shiyi Chen, Jiayu School of Information Science and Engineering Shenyang Ligong University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Science Shenyang China

ISBN: (纸本)9781510689176

Facial expressions are a challenging area in image recognition, and ensuring the universality of the model in the presence of a large sample size is a difficult point in such research. This article conducts repeatability experiments on two extreme scenarios: high-quality small samples and low-quality large samples, to explore solutions. Through transfer learning, data augmentation, and substantive evaluation of confusion matrices, the article demonstrates the accurate classification of seven facial expressions and the design of a 4-class model with high universality, which is presented in the form of an APP. © 2025 SPIE.

关键词： Deep learning

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Traffic sign recognition system based on YOLOv8-ConvNeXt

Traffic sign recognition system based on YOLOv8-ConvNeXt

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2024 International Conference on Mechatronic Engineering and Artificial Intelligence, MEAI 2024

作者： Qin, Lijuan Tang, Xiaoyu Fan, Chubin School of Information Science and Engineering Shenyang Ligong University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Science Shenyang China

ISBN: (纸本)9781510689176

In the context of road traffic safety, intelligent driver assistance systems are particularly important. During everyday driving, drivers are influenced by factors such as weather and fatigue, which can prevent them from quickly and accurately reacting to current traffic sign information. Therefore, to enable faster and more precise recognition, this paper designs an efficient traffic sign detection method. Image enhancement technology, particularly the Retinex algorithm, is introduced to improve the visual effect of images and enhance the separability of features. The introduction of the ConvNeXt V2 network further improves the detection speed and accuracy of the YOLOv8 model. Additionally, a self-collected dataset was supplemented to lay a good foundation for subsequent training. © 2025 SPIE.

关键词： Road and street markings

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