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IEEE International Conference on robotics and Automation (ICRA)

作者： Jan Fras Kaspar Althoefer Centre of Advanced Robotics @ Queen Mary (ARQ) Faculty of Science and Engineering Queen Mary University of London London UK

One of the biggest problems with soft robots is precisely the fact that they are soft. Indeed the softer they are, the less force they can exert on the environment. Researchers have proposed a number of stiffening methods, but all of them have drawbacks, such as locking the shape of the device in a way that precludes further adjustments. In this paper we propose a stiffening method inspired by the internal structure of the mammalian penis. The soft actuation chamber is divided into small compartments that trap the actuation fluid, leading to locally amplified pressure increase under certain conditions. At the same time, the proposed solution does not affect the actuation mechanism, allowing the actuator to be adjusted in one direction just as if it was in non-stiffened mode, while offering a stiff response in the opposite direction. Our prototype achieves an increase in stiffening of approximately a factor of two. The paper describes the concept, the mathematical justification of the working principle, the prototype design, its implementation and our experimental results.

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PCE: Multi-Agent Path Finding via Priority-Aware Communication & Experience Learning

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-13页

作者： Gao, Jianqi Li, Yanjie Ye, Zhaohui Wu, Xinyu Department of Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics and School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

Multi-agent path finding (MAPF) is an essential issue for warehouse automation, where multiple agents plan collision-free paths from the start to goal positions. Reinforcement learning (RL) has been employed to develop partially observable distributed MAPF methods that can be scaled to any number of agents. However, existing RL-based MAPF methods still have some limitations in handling redundant information and avoiding deadlock, resulting in a low success rate or longer makespan. This paper proposes a Priority-aware Communication & Experience learning method (PCE), which combines RL with a novel priority-aware multi-agent communication and a new priority-aware deadlock experience replay to tackle this challenge. To be specific, our innovation encompasses two-fold. Our proposed communication mechanism aims to handle redundant information, which establishes a dynamic communication topology based on agents' priorities and proposes a two-head priority-aware graph attention network to aggregate information. In order to help the agent avoid deadlock, we prioritize the expert experience that solves the deadlock when performing experience replay. We conduct multiple simulation experiments on warehouse-like structured grid maps. Compared with the state-of-the-art RL-based MAPF methods, PCE performs significantly better with a higher success rate and lower makespan in small and large MAPF and higher average throughput in the lifelong MAPF, which can further improve the efficiency of warehouse automation. Finally, we validate PCE using three Turtlebot3-Burger robots, which shows that PCE can be applied in real warehouse automation scenarios. IEEE

关键词： Aggregates

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Dissolvable temporary barrier:a novel paradigm for flexible hydrogel patterning in organ-on-a-chip models

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Bio-Design and Manufacturing 2024年第2期7卷 153-166页

作者： Ding Wang Qinyu Li Chenyang Zhou Zhangjie Li Kangyi Lu Yijun Liu Lian Xuan Xiaolin Wang Department of Micro/Nano Electronics School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Department of Ophthalmology LKS Faculty of MedicineThe University of Hong KongHong Kong 999077China Institute of Medical Robotics Shanghai Jiao Tong UniversityShanghai 200240China National Key Laboratory of Advanced Micro and Nano Manufacture Technology Shanghai Jiao Tong UniversityShanghai 200240China National Center for Translational Medicine(Shanghai)SHU Branch Shanghai UniversityShanghai 200444China

A combination of hydrogels and microfluidics allows the construction of biomimetic three-dimensional(3D)tissue models in vitro,which are also known as *** hydrogel patterningwith awell-controlled spatial distribution is typically achieved by embedding sophisticated microstructures to act as a ***,these physical barriers inevitably expose cells/tissues to a less physiologically relevant microenvironment than in vivo ***,we present a novel dissolvable temporary barrier(DTB)strategy that allows robust and flexible hydrogel patterning with great freedom of design and desirable flow stimuli for cellular *** key aspect of this approach is the patterning of a water-soluble rigid barrier as a guiding path for the hydrogel using stencil printing technology,followed by a barrier-free medium perfusion after the dissolution of the *** and multiple tissue compartments with different geometries can be established using either straight or curved DTB *** effectiveness of this strategy is further validated by generating a 3D vascular network through vasculogenesis and angiogenesis using a vascularized microtumor *** a new proof-of-concept in vasculature-on-a-chip,DTB enables seamless contact between the hydrogel and the culture medium in closed microdevices,which is an improved protocol for the fabrication ofmultiorgan ***,we expect it to serve as a promising paradigm for organ-on-a-chip devices for the development of tumor vascularization and drug evaluation in the future preclinical studies.

关键词： Dissolvable temporary barrier Hydrogel patterning Microfluidics Organ-on-a-chip Vascularization

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Learning Agile Quadrotor Flight in Restricted Environments with Safety Guarantees

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第9期9卷 1-8页

作者： Chen, Shiyu Li, Yanjie Lou, Yunjiang Lin, Ke Wu, Xinyu Department of Control Science and Engineering Harbin Institute of Technology Shenzhen and Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

With the increasing requirement for agile and efficient controllers in safety-critical scenarios, controllers that exhibit both agility and safety are attracting attention, especially in the aerial robotics domain. This paper focuses on the safety issue of Reinforcement Learning (RL)-based control for agile quadrotor flight in restricted environments. To this end, we propose a unified Adaptive Safety Predictive Corrector (ASPC) to certify each output action of the RL-based controller in real-time, ensuring its safety while maintaining agility. Specifically, we develop the ASPC as a finite-horizon optimal control problem, formulated by a variant of Model Predictive Control (MPC). Given the safety constraints determined by the restricted environment, the objective of minimizing loss of agility can be optimized by reducing the difference between the actions of RL and ASPC. As the safety constraints are decoupled from the RL-based control policy, the ASPC is plug-and-play and can be incorporated into any potentially unsafe controllers. Furthermore, an online adaptive regulator is presented to adjust the safety bounds of the state constraints with respect to the environment changes, extending the proposed ASPC to different restricted environments. Finally, simulations and real-world experiments are demonstrated in various restricted environments to validate the effectiveness of the proposed ASPC. IEEE

关键词： Reinforcement learning

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Autonomous Exploration of Mobile Robot Equipped with Lidar for High-Quality Reconstruction in Large-Scale Indoor Environments

SSRN

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SSRN 2025年

作者： Shih, Pin-Chu Chiang, Yun-Chi Hu, Jun-Jie Fu, Li-Chen Department of Electrical Engineering National Taiwan University Taipei100 Taiwan NTU Center for Artificial Intelligence and Advanced Robotics National Taiwan University Taipei100 Taiwan

High-quality 3D reconstruction is essential for ap- plications such as autonomous driving, AR/VR, and smart cities. Traditional methods using handheld sensors often result in incomplete and misaligned models. While autonomous explo- ration can improve these results, it often sacrifices quality for speed. In this paper, we propose a system for high-quality 3D reconstruction of large-scale indoor environments through autonomous exploration using a mobile robot equipped with a solid-state LiDAR on a 2-degree-of-freedom gimbal. This system not only controls the mobile robot to visit unknown places and areas with insufficient reconstruction quality but also facilitates high-frequency, real-time exploration path planning. This paper concludes with various simulations and real-world experiments to validate the effectiveness of our system. © 2025, The Authors. All rights reserved.

关键词： 3D reconstruction

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Formation Control of Unmanned Underwater Vehicles With Unknown Absolute Position Using Rigid Graph-Based MPC

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IEEE Internet of Things Journal 2025年

作者： Fu, Bowen Zhu, Daqi Chen, Mingzhi Yang, Simon X. University of Shanghai for Science and Technology Shanghai200093 China University of Guelph Advanced Robotics and Intelligent Systems Laboratory School of Engineering GuelphONN1G2W1 Canada

Formation control of unmanned underwater vehicles (UUVs) is of great significance to the Internet of Underwater Things (IoUT). Currently, various methods are employed for UUV formation control. Among them, rigid graph-based approaches, which rely solely on relative information between UUVs, are particularly suitable for underwater environments. However, traditional rigid graph-based formation control methods often face challenges such as control jumps and weak robustness in dynamic underwater environments. To address these challenges, a novel rigid graph-based model predictive controller (RGMPC) is proposed in this paper. The proposed approach integrates model predictive control with traditional rigid graph-based methods, effectively avoiding issues such as control jumps and thrust saturation while enhancing robustness. Moreover, constraints are constructed using backstepping methods to theoretically ensure the closed-loop stability of the algorithm. Finally, the algorithm is validated through extensive simulations based on mathematical models and further tested in the Gazebo simulator, fully demonstrating its feasibility and effectiveness. © 2014 IEEE.

关键词： Predictive control systems

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Design and Manufacturing of an Intelligent Ping-Pong Robot (RoboPing)

Design and Manufacturing of an Intelligent Ping-Pong Robot (...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： S. Ali A. Moosavian Arian D. Farahani Ali Karimi Advanced Robotics and Automated Systems (ARAS) Lab. Dept of Mechanical Engineering Center of Excellence in Robotics and Control K. N. Toosi University of Technology Tehran Iran

robotics and artificial intelligence (AI) are rapidly transforming many industries and aspects of our lives, and sport activities are no exception. Robots and AI are already being used in a variety of sports, including training and performance analysis. This paper introduces a new assistant ping-pong robot (RoboPing) that shoots ping-pong balls with different speeds and spins, besides using AI to analyze training sessions and providing useful insights into the game. RoboPing represents a significant advancement in mechanical design over previous versions, offering enhanced functionality. Being equipped with a precise vision system makes RoboPing more advanced compared to existing versions.

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UDE based RISE Controller for Active Flutter Suppression of 2D Aerofoil 18

UDE based RISE Controller for Active Flutter Suppression of ...

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18th IEEE India Council International Conference, INDICON 2021

作者： Sharma, Balraj DIxit, Abhishek Agrawal, Pooja Misra, Ajay Defence Institute of Advanced Technology Dept of Aerospace Engineering Pune411025 India Defence Institute of Advanced Technology School of Robotics Pune411025 India

ISBN: (纸本)9781665441759

In this paper, active flutter suppression (AFS) of a typical two dimensional aerofoil using a new continuous control technique, called Robust Integral of Signum of Error (RISE) is proposed. The aerofoil model involves two degrees of freedom of motion i.e. pitch and plunge. To enhance the performance of controller in presence of parametric uncertainty and external disturbances, RISE controller has been robustified by designing an uncertainty and disturbance estimator (UDE), which will estimate the total lumped disturbances. The controller does not require any knowledge of plant model or information of uncertainty and disturbances. The efficacy of UDE based RISE controller has been illustrated by simulations using parametric uncertainty, external disturbances, time delay, variation in free stream velocity and constraint of control surface deflection. Results show that proposed controller has enhanced the performance of closed loop system by 68% beyond critical flutter speed. Performance comparison of proposed design has been carried out with UDE based SMC controller which prove the effectiveness of proposed design. Lastly, results indicate that UDE based RISE controller has drastically reduced the rise time, settling time and also, control efforts have been reduced by upto 75% in comparison to UDE based SMC controller. © 2021 IEEE.

关键词： Controllers

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Landing Area Prediction in Complex Terrains for Walking-assisted Lower-limb Exoskeleton Robot

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Procedia Computer Science 2023年 226卷 120-126页

作者： Yuexun Liu Du-Xin Liu Yue Ma Sheng Guo Xinyu Wu Robotics Research Center School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing 100044 China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China

With the expansion of application scenarios, the walking-assisted lower-limb exoskeleton robot urgently needs to improve its walking ability in complex terrains. However, due to the lack of environmental understanding ability and decision-making ability, the exoskeleton can not meet the need of people with lower-limb disability in complex terrains. To improve the walking abillity, this paper proposes a method of predicting the landing area in complex terrains for walking-assisted lower-limb exoskeleton robot. Multiple sensors were used to obtain the terrain information, step length, and stride length of human walking, and a multi-type input convolutional network was built to establish the mapping relationship to learn the decision-making mechanism of human standing in a complex environment. The result shows that the established network effectively predicts the landing area. Under the condition of full training, the predicted position deviation of the landing area is controlled within 6%, and the prediction rationality of the landing area can reach 90%.

关键词： Landing area prediction Walking-assisted lower-limb exoskeleton robot Complex terrains

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Optimization of rotor blind hole parameters for inner-hole rotary cavitator 4

Optimization of rotor blind hole parameters for inner-hole r...

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4th IAHR Asian Working Group Symposium on Hydraulic Machinery and Systems

作者： Li, Dawei Yang, Yingjie Ge, Ning Han, Guihua Zhu, Yipeng Jin, Di Institute of Advanced Technology Heilongjiang Academy of Sciences Harbin150020 China School of Mechanical and Power Engineering Harbin University of Science and Technology Harbin150080 China XJ Electric Co. Ltd. Xuchang461000 China Ningbo Lotus Robotics Co. Ltd. Ningbo310051 China

In order to study the cavitation characteristics of rotary cavitator and the optimization of blind hole parameters, this paper first deduces the blind hole geometric parameters (aperture, hole depth, and number of holes) that affect the cavitation effect, then uses a numerical simulation method to optimize the blind hole parameters that affect the cavitation effect based on the control variable method and gas phase contour. Using single factor analysis as the optimization criterion and gas phase volume as the optimization basis, the response surface method was applied to the multi-parameter optimization problem with interaction. The results indicate that the intensity of cavitation can be effectively increased by increasing the geometric dimensions of the blind holes' diameter, depth, and number appropriately. On the other hand, the response surface method can be utilised to study the multi-parameter optimization problem in the multivariable system comprised of the geometric parameters of the blind hole of the cavitator rotor. This paper's optimization research on the rotor parameters of inner-hole rotary cavitator provides a foundation and reference for future cavitator structure optimization research. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Numerical methods

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