Bohan Feng

Shanghai Jiao Tong University

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Youyi Bi

Shanghai Jiao Tong University

Weiyu Song

China University of Petroleum, Beijing

Chunming Xu

China University of Petroleum, Beijing

Jian Liu

China University of Petroleum, Beijing

Yuechang Wei

China University of Petroleum, Beijing

Jing Xiong

Union Hospital

Qi Zhou

Shanghai Academy of Spaceflight Technology

Zhen Zhao

China University of Petroleum, Beijing

Dong Li

Third Affiliated Hospital of Zhengzhou University

Xinting Jiang

Shanghai Jiao Tong University

Cooperative Institutions

Shanghai Jiao Tong University

China University of Petroleum, Beijing

Chinese Academy of Sciences

State Key Laboratory of Heavy Oil

Fudan University

Centre National de la Recherche Scientifique

Université Paris-Saclay

University of Science and Technology Beijing

Synchrotron soleil

University of Geneva

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Unraveling the real active site of reaction-induced trivalent vanadium ion in VOx/Al2O3 catalysts for boosting photothermal catalytic propane non-oxidative dehydrogenation

Applied Catalysis B Environment and Energy (2022)

Bohan Feng Dong Li Jing Xiong Yuechang Wei Yuanfeng Li

Propane

Vanadium Oxide

10.1016/j.apcatb.2022.122337

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Citations (10)

An adaptive multi-RRT approach for robot motion planning

Expert Systems with Applications (2024)

Bohan Feng Xinting Jiang Boyan Li Qi Zhou Youyi Bi

10.1016/j.eswa.2024.124281

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Citations (3)

Ordered Hierarchical Porous Structure of PtSn/3DOMM-Al2O3 Catalyst for Promoting Propane Non-Oxidative Dehydrogenation

Nanomaterials (2023)

Yuanqing Sun Bohan Feng Qian Lian Chengshu Xie Jing Xiong

Herein, the hierarchical porous catalyst of 3-dimensional ordered macro-mesoporous (3DOMM) Al2O3 supported active PtSn nanoparticles (NPs) was prepared by the combined synthesized path of evaporation-induced self-assembly with colloid crystal template (EISA-CCT) methods. The hierarchical macro-mesoporous composite structure can markedly increase the specific surface area, accommodate the diffusion of propene, and decrease the number of surface acid sites. In addition, the special surface property and pore structure of 3DOMM-Al2O3 can modify the interaction between metals and substrates, as well as stabilize the metal nanoparticle, which promotes the formation of a highly active and stable PtSn phase. The PtSn/3DOMM-Al2O3 catalyst exhibits higher productivity and stability than PtSn/Al2O3 catalysts with macropore and mesopore structures. The PtSn/3DOMM-Al2O3 catalyst displays the best catalytic performance with propylene selectivity over 95% at a propane conversion of 33.9%. The study of the ordered hierarchical porous structure of PtSn/3DOMM-Al2O3 catalysts can contribute to obtaining improved catalysts in industrial processes.

Propene

Specific surface area

Propane

10.3390/nano13040728

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Citations (2)

An intelligent spinal soft robot with self-sensing adaptability

The Innovation (2024)

Shoulu Gong Fuyi Fang Zhiran Yi Bohan Feng Anyu Li

Self-sensing adaptability is a high-level intelligence in living creatures and is highly desired for their biomimetic soft robots for efficient interaction with the surroundings. Self-sensing adaptability can be achieved in soft robots by the integration of sensors and actuators. However, current strategies simply assemble discrete sensors and actuators into one robotic system and, thus, dilute their synergistic and complementary connections, causing low-level adaptability and poor decision-making capability. Here, inspired by vertebrate animals supported by highly evolved backbones, we propose a concept of a bionic spine that integrates sensing and actuation into one shared body based on the reversible piezoelectric effect and a decoupling mechanism to extract the environmental feedback. We demonstrate that the soft robots equipped with the bionic spines feature locomotion speed improvements between 39.5% and 80% for various environmental terrains. More importantly, it can also enable the robots to accurately recognize and actively adapt to changing environments with obstacle avoidance capability by learning-based gait adjustments. We envision that the proposed bionic spine could serve as a building block for locomotive soft robots toward more intelligent machine-environment interactions in the future.

Adaptability

Decoupling (probability)

10.1016/j.xinn.2024.100640

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Citations (2)

Did monetary policy cause a housing bubble in the US?

BCP Business & Management (2022)

Bohan Feng

This article uses quantitative analysis, setting three variables: the federal funds rate, mortgage servicing as a percentage of disposable personal income, and house prices. I made a simple model using the logical relationship of the independent variable, mediator variable, and dependent variable. Then regression analysis is conducted to explore the relationship between monetary policy and real estate bubbles. The conclusion is that loose monetary policy contributed to the housing bubble, but raising the federal funds rate did not contain the rise in housing prices, which means the existing monetary policy tools are insufficient to solve the problem. A better regulatory system is needed to avoid the emergence of bubble economies.

Variables

Economic bubble

10.54691/bcpbm.v29i.2295

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An Efficient Space Spatiotemporal Noise Filter for Dynamic Vision Sensor

2021 IEEE 14th International Conference on ASIC (ASICON) (2021)

Bohan Feng Xi En Cheng Jingjing Liu Mingyu Wang Wenhong Li

In order to improve the denoising performance of dynamic vision sensor, an efficient space spatiotemporal noise filter (ESSNF) is proposed in this paper, which achieved excellent results in the performance index of normalized variance. Firstly, the manhattan distance and adaptive weight are utilized to describe the spatiotemporal correlation of events. Secondly, The experiment was evaluated by normalized variance(NV), which is a new evaluation indicator and the noise event follows a Poisson distribution. Finally, the experimental results show that ESSNF can effectively remove noise events and retain real events compared with other methods.

10.1109/asicon52560.2021.9620254

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A robotic manipulation framework for industrial human–robot collaboration based on continual knowledge graph embedding

The International Journal of Advanced Manufacturing Technology (2024)

Bohan Feng Xinzhe Juan Xinyi Gao Qi Zhou Youyi Bi

Knowledge graph

Human–robot interaction

10.1007/s00170-024-14468-w

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A Soft Collaborative Robot for Contact‐based Intuitive Human Drag Teaching

Advanced Science (2024)

Shoulu Gong Wenbo Li Jiahao Wu Bohan Feng Zhiran Yi

Abstract Soft material‐based robots, known for their safety and compliance, are expected to play an irreplaceable role in human‐robot collaboration. However, this expectation is far from real industrial applications due to their complex programmability and poor motion precision, brought by the super elasticity and large hysteresis of soft materials. Here, a soft collaborative robot (Soft Co‐bot) with intuitive and easy programming by contact‐based drag teaching, and also with exceptional motion repeatability (< 0.30% of body length) and ultra‐low hysteresis (< 2.0%) is reported. Such an unprecedented capability is achieved by a biomimetic antagonistic design within a pneumatic soft robot, in which cables are threaded to servo motors through tension sensors to form a self‐sensing system, thus providing both precise actuation and dragging‐aware collaboration. Hence, the Soft Co‐bots can be first taught by human drag and then precisely repeat various tasks on their own, such as electronics assembling, machine tool installation, etc. The proposed Soft Co‐bots exhibit a high potential for safe and intuitive human‐robot collaboration in unstructured environments, promoting the immediate practical application of soft robots.

Soft Robotics

Soft materials

10.1002/advs.202308835

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Citations (2)

An Integrated Task and Path Planning Approach for Mobile Robots in Smart Factory

Volume 2B: Advanced Manufacturing (2022)

Shuo Liu Bohan Feng Dan Yu Youyi Bi

Abstract Mobile robots are being widely used in smart manufacturing, and efficient task assignment and path planning for these robots is an area of high interest. In previous studies, task assignment and path planning are usually solved as separate problems, which can result in optimal solutions in their respective fields, but not necessarily optimal as an integrated problem. Meanwhile, precedence constraints exist between sequential processing operations and material delivery tasks in the manufacturing environment. Thus, those planning methods developed for warehousing and logistics may not simply apply to the environment of smart factories. In this paper, we propose an integrated task and path planning approach based on Looking-backward Search Strategy (LSS) and Regret-based Search Strategy (RSS). In the stage of task assignment, the real paths for mobile robots are identified based on the Cooperative A* (CA*) algorithm and the time and energy consumed by mobile robots and machining centers are calculated. Then a greedy strategy working with LSS or RSS is used to search reasonable task assignments in time-series, which can generate a joint optimal solution for both task assignment and path planning. We verify the validity of the proposed approach in a simulated smart factory and the results show that our approach can improve the operation efficiency of the smart factory and save the time and energy consumption effectively.

Factory (object-oriented programming)

RSS

10.1115/imece2022-95364

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Citations (1)

BRMPNet: bidirectional recurrent motion planning networks for generic robotic platforms in smart manufacturing

Advances in Manufacturing (2024)

Bohan Feng Boyan Li Xinting Jiang Qi Zhou Youyi Bi

Smart Manufacturing

10.1007/s40436-024-00529-6

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