Article
Chemistry, Multidisciplinary
Ivan Virgala, L'ubica Mikova, Tatiana Kelemenova, Martin Varga, Robert Rakay, Marek Vagas, Jan Semjon, Rudolf Janos, Marek Sukop, Peter Marcinko, Peter Tuleja
Summary: The paper discusses a proposed concept for a biped robot that has vertical stabilization and minimizes sideways oscillation. It can be used as a mechatronic assistant or as a carrier for handling extensions.
APPLIED SCIENCES-BASEL
(2022)
Article
Automation & Control Systems
Daojin Yao, Lin Yang, Xiaohui Xiao, MengChu Zhou
Summary: This article develops a gait planning method for underactuated bipedal robot to walk on uneven and compliant terrain by controlling and tracking the robot's CoM and desired velocity.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Computer Science, Artificial Intelligence
Huthaifa Ahmad, Yoshihiro Nakata, Yutaka Nakamura, Hiroshi Ishiguro
Summary: This study introduces the development of a bipedal robot with adaptive morphology, enabling it to adjust its physical characteristics of legs and their interactions through an actuator network system. The main and supplementary experiments show that adjusting the robot's morphology can change its behavior to adapt to different environments.
Article
Engineering, Mechanical
Linqi Ye, Xueqian Wang, Houde Liu, Bin Liang, Bo Yuan
Summary: This paper investigates how to walk faster for two simple 2D walking models. Open-loop analysis is conducted and the concept of acceleration factor is proposed. It is found that the acceleration factor has a fixed correlation with the velocity transition trend, independent of the step length. Based on this, walking controllers are designed and closed-loop simulations are performed to achieve faster walking speeds.
NONLINEAR DYNAMICS
(2023)
Article
Robotics
Erman Selim, Musa Alci, Mert Altintas
Summary: A variable time interval trajectory optimization method is proposed in this study to increase the optimization accuracy and reduce the cost of transport for walking robots.
Article
Multidisciplinary Sciences
German Pequere, Ignacio Ramirez Paulino, Carlo M. Biancardi
Summary: This study investigated the muscle activation patterns in unilateral skipping and found similarities with symmetrical gaits. The different timing of muscle synergy activation between leading and trailing limbs in unilateral skipping may be a key factor that distinguishes it from walking or running.
Article
Biotechnology & Applied Microbiology
Daisuke Ichimura, Hiroaki Hobara, Genki Hisano, Tsubasa Maruyama, Mitsunori Tada
Summary: This study investigated how individuals with unilateral transtibial amputation control their left and right lower limbs during locomotion and found that they can reacquire locomotion by modifying sensory feedback parameters. These results are important for assessing and rehabilitating the walking ability of individuals with unilateral transtibial amputation.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Changxin Huang, Guangrun Wang, Zhibo Zhou, Ronghui Zhang, Liang Lin
Summary: Controlling a non-statically bipedal robot is challenging, but this study proposes a novel reward-adaptive reinforcement learning method for biped locomotion. By using a dynamic mechanism, the control policy can be simultaneously optimized by multiple criteria. The proposed method utilizes a multi-head critic to learn a separate value function for each reward component, resulting in hybrid policy gradients. Experimental results demonstrate the effectiveness and generalization of this approach.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Computer Science, Information Systems
Michele Folgheraiter, Asset Yskak, Sharafatdin Yessirkepov
Summary: This study identifies the nonlinear inverted pendulum model of a lightweight bipedal robot in real-time using a reservoir-based Recurrent Neural Network (RNN). The adaptation algorithm is proven to converge based on Lyapunov stability criteria. Results show that the RNN model, when trained with only a few examples of the disturbance response, achieves a Mean Squared Error (MSE) of 0.0048 on a normalized validation set, outperforming a linear ARX model and a more sophisticated NNARX model. The computational complexity of the RNN model with the RLS adaptation algorithm is lower compared to the NNARX model with backpropagation, making it more suitable for real-time applications.
Article
Chemistry, Multidisciplinary
Phan Bui Khoi, Hong Nguyen Xuan
Summary: This paper investigates the problem of controlling a human-like bipedal robot during walking and proposes a method for building a fuzzy rule system suitable for bipedal robot control. By analyzing dynamical factors and designing motion trajectories, informational data and parameters are provided for the determination of the controller.
APPLIED SCIENCES-BASEL
(2021)
Article
Biology
Baruch Haimson, Yoav Hadas, Nimrod Bernat, Artur Kania, Monica A. Daley, Yuval Cinnamon, Aharon Lev-Tov, Avihu Klar
Summary: Peripheral and intraspinal feedback are crucial for shaping and updating spinal networks that control motor behavior. dI2 spinal interneurons in chicks receive synaptic input from afferents and premotor neurons, and are involved in local spinal circuits and lumbo-brachial coupling. Silencing these neurons results in destabilized stepping and wide-base walking gait in hatchlings, indicating their contribution to bipedal gait stabilization.
Review
Chemistry, Analytical
Tadeusz Mikolajczyk, Emilia Mikolajewska, Hayder F. N. Al-Shuka, Tomasz Malinowski, Adam Klodowski, Danil Yurievich Pimenov, Tomasz Paczkowski, Fuwen Hu, Khaled Giasin, Dariusz Mikolajewski, Marek Macko
Summary: This review presents the latest developments of bipedal walking robots based on natural bipedal movements and innovative synthetic solutions. It provides an overview of scientific analysis of human gait and discusses the problem of balance and energy demand. It also reviews various types of bipedal robot solutions including nature-inspired robots and innovative robots. The future of bipedal robots is discussed in relation to conventional and synthetic unconventional gait.
Article
Engineering, Biomedical
Amre Eizad, Hosu Lee, Sanghun Pyo, Min-Kyun Oh, Sung-Ki Lyu, Jungwon Yoon
Summary: This study evaluated the effects of different footrest configurations on balance performance, trunk movement, and muscle activation under different seating scenarios. The results suggest that a seat-connected footrest is suitable for balance recovery rehabilitation, while a ground-mounted footrest is suitable for trunk movement-focused rehabilitation. Careful selection of seat and footrest conditions can potentially target specific muscle groups during training.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2022)
Article
Robotics
Kyunam Kim, Patrick Spieler, Elena-Sorina Lupu, Alireza Ramezani, Soon-Jo Chung
Summary: LEONARDO is a multimodal locomotion robotic platform that combines flying and walking through synchronized control, achieving complex maneuvers and unique locomotion capabilities to tackle various challenging tasks.
Review
Thermodynamics
Jinman Zhou, Shuo Yang, Qiang Xue
Summary: Lower limb rehabilitation exoskeleton robots (LLRERs) play a positive role in rehabilitation and assistance for patients with lower limb disorders, with a need for further research and improvement to enhance adaptability and clinical significance.
ADVANCES IN MECHANICAL ENGINEERING
(2021)
Article
Chemistry, Multidisciplinary
Siqi Sun, Jiaqi Miao, Rong Tan, Tieshan Zhang, Gen Li, Yajing Shen
Summary: This study presents an asymmetric soft-structure functional surface (ASFS) that can directionally transport liquids, achieve liquid mixing, and has intelligent response ability by utilizing the intrinsic properties of the liquids. It opens new avenues for application-oriented liquid operation surfaces.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Article
Nanoscience & Nanotechnology
Zhenghua Zhao, Mingjie Liu, Kai Zhou, Lidong Guo, Yajing Shen, Dan Lu, Xin Hong, Zongbi Bao, Qiwei Yang, Qilong Ren, Peter R. Schreiner, Zhiguo Zhang
Summary: Phenoxyl radicals derived from phenols have been harnessed for photocatalysis due to their stability and mild oxidative activity. A stable and recyclable metal-organic framework Zr-MOF-OH, composed of a binaphthol derivative ligand, has been synthesized and shown to function as an efficient heterogeneous photocatalyst with good catalytic activity and substrate compatibility for the selective oxidation of sulfides to sulfoxides under visible light irradiation. The photocatalytic process involves the conversion of phenolic hydroxyl groups to phenoxyl radicals through excited state intramolecular proton transfer, with triplet O2 directly participating in the reaction, providing wide substrate compatibility and high selectivity.
ACS APPLIED MATERIALS & INTERFACES
(2023)
Article
Chemistry, Multidisciplinary
Chang Xu, Yali Liu, Jiayan Li, Peng Ning, Zhong Shi, Wei Zhang, Zhenguang Li, Ruimei Zhou, Yifan Tong, Yingze Li, Cheng Lv, Yajing Shen, Qian Cheng, Bin He, Yu Cheng
Summary: This study proposes a photomagnetically powered nanomachine (PMN) with a spiky surface and thermally dependent viscosity tunability to facilitate mechanical motion in lysosomes for cancer mechanotherapy. The spiky structure endows nanomachines with a photomagnetic coupling effect in the NIR-II region, and PMNs can be efficiently propelled under simultaneously applied dual external energy sources in cell lysosomes. Enhanced mechanical destruction of cancer cells via PMNs is confirmed both in vitro and in vivo under photomagnetic treatment. This study provides a theoretical basis for designing integrated nanomachines with active adaptability to physiological environments for cancer treatment.
ADVANCED MATERIALS
(2023)
Article
Chemistry, Physical
Zhihao Jin, Yajing Shen, Xianfu Chen, Minghui Qiu, Yiqun Fan
Summary: The introduction of Ce effectively inhibited the phase transformation of TiO2 and prevented cracks, resulting in excellent performance and anti-fouling properties for the Ce-doped TiO2 membrane in protein separation.
APPLIED SURFACE SCIENCE
(2023)
Article
Chemistry, Analytical
Tieshan Zhang, Gen Li, Xiong Yang, Hao Ren, Dong Guo, Hong Wang, Ki Chan, Zhou Ye, Tianshuo Zhao, Chengfei Zhang, Wanfeng Shang, Yajing Shen
Summary: This study presents a millimeter-scale magnetic-polymer-based modular continuum catheter robot (MMCCR) that can perform various bending with a fast and versatile modular fabrication strategy. By preprogramming the magnetization directions of two simple magnetic units, the assembled MMCCR can transform from a single curvature pose to a multicurvature S shape in the applied magnetic field. Through static and dynamic deformation analyses, high adaptability to different confined spaces is predicted for MMCCRs. Using a bronchial tree phantom, the proposed MMCCRs demonstrated their capability to adaptively access channels with challenging geometries.
Article
Engineering, Multidisciplinary
Jiaqi Miao, Tieshan Zhang, Gen Li, Dong Guo, Siqi Sun, Rong Tan, Jiahai Shi, Yajing Shen
Summary: This article investigates the motion styles of flagella and cilia and proposes a unified physical model to describe their bending and external motions. The study deepens our understanding of microorganisms' propulsion mechanism and provides new inspirations for biomimetic system design.
Article
Engineering, Civil
Xing Li, Zhenlong Hu, Yajing Shen, Lina Hao, Wanfeng Shang
Summary: The purpose of this study is to optimize the Beetle Antenna Search (BAS) algorithm and apply it to the Intelligent Transportation System (ITS) to address traffic congestion. The study examines the development status of ITS and the application status of the BAS algorithm. It proposes an algorithm with quadratic interpolation optimization, named QIBAS, combined with the Least Squares Support Vector Machine Algorithm (LSSVM). A traffic flow prediction model based on QIBAS-LSSVM is established. The results show that the proposed QIBAS algorithm has a good effect and high accuracy in short-term traffic flow prediction.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Xing Li, Haotian Zhang, Yajing Shen, Lina Hao, Wanfeng Shang
Summary: This study aims to improve the transmission and sharing efficiency of intelligent transportation data and promote the further development of intelligent transportation and smart city. Through the design of the Energy Efficient Multi-hop Routing (EEMR) algorithm and the deep learning-based TAdam algorithm, the energy balance of network nodes and the minimization of system energy consumption have been achieved. The experimental results show that the EEMR algorithm achieves a network surviving node proportion of over 90% in data collection, while the TAdam algorithm exhibits the fastest convergence speed and the best generalization performance on the test data set.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Information Systems
Xiuping Nie, Lilu Liu, Lifeng He, Liang Zhao, Haojian Lu, Songmei Lou, Rong Xiong, Yue Wang
Summary: In order to overcome the lack of large-scale pixel-level annotated datasets in common medical image segmentation tasks, a novel Weakly-Interactive-Mixed Learning (WIML) framework is proposed to achieve the desired segmentation accuracy by efficiently using weak labels. The framework includes a Weakly-Interactive Annotation (WIA) part to reduce annotation time and a Mixed-Supervised Learning (MSL) part to boost segmentation accuracy. A Full-Parameter-Sharing Network (FPSNet) with attention modules (scSE) and a Full-Parameter-Sharing (FPS) strategy are also proposed to implement this framework.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Robotics
Xuecheng Xu, Sha Lu, Jun Wu, Haojian Lu, Qiuguo Zhu, Yiyi Liao, Rong Xiong, Yue Wang
Summary: Global localization is crucial in robot applications, and LiDAR-based global localization stands out for its robustness against illumination and seasonal changes. We propose RING++, a learning-free framework with roto-translation-invariant representation and global convergence for rotation and translation estimation, which can address large viewpoint differences using a lightweight map with sparse scans. Our approach, the first of its kind, accomplishes all subtasks of global localization in sparse scan maps and outperforms state-of-the-art learning-free methods, competing with learning-based methods.
IEEE TRANSACTIONS ON ROBOTICS
(2023)
Article
Automation & Control Systems
Jingyu Zhang, Qin Fang, Pingyu Xiang, Lilu Liu, Rong Xiong, Yue Wang, Haojian Lu
Summary: Lung disease is a major cause of disease-related death and a serious global health problem. The traditional biopsy operation for lung diseases has limitations due to the size and flexibility of the bronchoscope and the lack of force sensing. This article proposes a flexible biopsy robot with force-sensing ability, which has the potential to improve the diagnosis rate of lung diseases and reduce related deaths.
ADVANCED INTELLIGENT SYSTEMS
(2023)
Article
Automation & Control Systems
Qin Fang, Jingyu Zhang, Danying Sun, Yanan Xue, Rui Jin, Nenggan Zheng, Yue Wang, Rong Xiong, Zhefeng Gong, Haojian Lu
Summary: In this study, an integrated design and fabrication strategy is proposed for a soft lightweight (3.5 g) small-scale (phi 60x40 mm) parallel robot based on the dielectric elastomer actuator. A hybrid model is established to describe the mapping between driving space and workspace, utilizing the robustness of the model-based method and the nonlinear fitting ability of the data-driven neural network method. The stiffness and workspace of the robot are analyzed. Trajectory tracking experiments demonstrate the accuracy and robustness of the proposed hybrid model, with an average positioning error of 13.4-16.6 μm. Finally, a zebrafish embryo puncture experiment is conducted to showcase the micromanipulation ability. This research opens up new possibilities for designing and controlling high-positioning soft parallel robots for applications in the micromanipulation field.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Automation & Control Systems
Pingyu Xiang, Jingyu Zhang, Danying Sun, Ke Qiu, Qin Fang, Xiangyu Mi, Yue Wang, Rong Xiong, Haojian Lu
Summary: This paper proposes a learning-based high-precision force estimation method for small-scale continuum robot, enabling compliant control and high-precision force tracking. Experimental results validate the effectiveness of the proposed method in fitting the mechanical model of the robot and improving the precision of force control.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
