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Generative Adversarial Network Based Heuristics for Sampling-Based Path Planning

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 64-74页

作者： Tianyi Zhang Jiankun Wang Max Q.-H.Meng Department of Electronic and Electrical Engineering Southern University of Science and TechnologyShenzhen 518055China

Sampling-based path planning is a popular methodology for robot path planning.With a uniform sampling strategy to explore the state space,a feasible path can be found without the complex geometric modeling of the configuration space.However,the quality of the initial solution is not guaranteed,and the convergence speed to the optimal solution is slow.In this paper,we present a novel image-based path planning algorithm to overcome these limitations.Specifically,a generative adversarial network(GAN)is designed to take the environment map(denoted as RGB image)as the input without other preprocessing works.The output is also an RGB image where the promising region(where a feasible path probably exists)is segmented.This promising region is utilized as a heuristic to achieve non-uniform sampling for the path planner.We conduct a number of simulation experiments to validate the effectiveness of the proposed method,and the results demonstrate that our method performs much better in terms of the quality of the initial solution and the convergence speed to the optimal solution.Furthermore,apart from the environments similar to the training set,our method also works well on the environments which are very different from the training set.

关键词： Generative adversarial network(GAN) optimal path planning robot path planning sampling-based path planning

Relevant Region sampling strategy with adaptive heuristic for asymptotically optimal path planning

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Biomimetic intelligence & robotics 2023年第3期3卷 21-29页

作者： Chenming Li Fei Meng Han Ma Jiankun Wang Max Q-H.Meng Department of Electronic Engineering The Chinese University of Hong KongHong Kong 999077China Department of Electronic and Electrical Engineering Southern University of Science and TechnologyShenzhen 518055China shenzhen Research Institute of the Chinese University of Hong Kong Shenzhen 518057China

Sampling-based planning algorithm is a powerful tool for solving planning problems in highdimensional state spaces.In this article,we present a novel approach to sampling in the most promising regions,which significantly reduces planning time-consumption.The RRT#algorithm defines the Relevant Region based on the cost-to-come provided by the optimal forward-searching tree.However,it uses the cumulative cost of a direct connection between the current state and the goal state as the cost-to-go.To improve the path planning efficiency,we propose a batch sampling method that samples in a refined Relevant Region with a direct sampling strategy,which is defined according to the optimal cost-to-come and the adaptive cost-to-go,taking advantage of various sources of heuristic information.The proposed sampling approach allows the algorithm to build the search tree in the direction of the most promising area,resulting in a superior initial solution quality and reducing the overall computation time compared to related work.To validate the effectiveness of our method,we conducted several simulations in both SE(2)and SE(3)state spaces.And the simulation results demonstrate the superiorities of proposed algorithm.

关键词： Path planning Asymptotical optimality Relevant Region Adaptive heuristic

Polarization-controlled dual resonant lattice Kerker effects

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Nano Research 2023年第2期16卷 3195-3200页

作者： Lei Xiong Xueqian Zhao Xiang Du Shuai Chen Yuanfu Lu Hongwei Ding Guangyuan Li School of Information Science and Engineering Yunnan UniversityKunming 650500China CAS key laboratory of Human-Machine intelligence-Synergy Systems Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China School of Computer Electronic and InformationGuangxi UniversityNanning 530004China College of Physics and Electronic Technology Anhui Normal UniversityWuhu 241000China Tianjin H-Chip Technology Group Corporation Tianjin 300467China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for SocietyShenzhen 518055China

The generalized Kerker effects have attracted increasing interests in recent years due to their abilities to manipulate the far-field properties of metasurfaces.However,the dual-polarized generalized Kerker effect enabling different tailoring of orthogonally-polarized electromagnetic waves has not yet been reported.Herein,we demonstrate polarization-controlled dual resonant lattice Kerker effects in periodic silicon nanodisks.By varying the incident angle,the electric dipole and magnetic dipole surface lattice resonances can spectrally overlap,causing zero reflectance and unitary transmittance,i.e.,the resonant lattice Kerker effect.The incident angle for achieving this effect can be tuned differently for s-and p-polarizations over large regions by varying the nanodisk size or the lattice periods.The proposed dual-polarized resonant lattice Kerker effects open up avenues for polarization-controlled manipulation of the phase and wavefront of light with metasurfaces.

关键词： Kerker effect surface lattice resonances dual-polarized silicon metasurface

Hierarchical policy with deep-reinforcement learning for nonprehensile multiobject rearrangement

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Biomimetic intelligence & robotics 2022年第3期2卷 1-8页

作者： Fan Bai Fei Meng Jianbang Liu Jiankun Wang Max Q-H.Meng Department of Electronic Engineering The Chinese University of Hong KongShatin N.T.Hong Kong SARChina Department of Electronic and Electrical Engineering Southern University of Science and TechnologyShenzhenChina shenzhen Research Institute of the Chinese University of Hong Kong ShenzhenChina

Nonprehensile multiobject rearrangement is the robotic task of planning feasible paths and transferring multiple objects to their predefined target poses without grasping.It must consider how each object reaches the target and the order in which objects move,considerably increasing the complexity of the problem.Thus,we propose a hierarchical policy for nonprehensile multiobject rearrangement based on deep-reinforcement learning.We use imitation learning and reinforcement learning to train a rollout policy.In a high-level policy,the policy network directs the Monte Carlo tree search algorithm to efficiently seek the ideal rearrangement sequence for several items.In a low-level policy,the robot plans the paths according to the order of path primitives and manipulates the objects to approach the target poses one by one.Our experiments show that the proposed method has a higher success rate,fewer steps,and shorter path length than the state-of-the-art methods.

关键词： Rearrangement Reinforcement learning Monte Carlotreesearch

A review of bio-inspired needle for percutaneous interventions

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Biomimetic intelligence & robotics 2022年第4期2卷 2-13页

作者： Yichi Ma Xiao Xiao Hongliang Ren Max Q.-H.Meng Department of Mechanical Engineering University of CaliforniaBerkeley 94720USA Department of Electronic and Electrical Engineering Southern University of Science and TechnologyShenzhen 518055China Department of Electronic Engineering The Chinese University of Hong KongHongkong 999077China

Bio-inspired design translates the knowledge of natural or biological structures or behaviors into novel theories and technologies,providing new directions for research and developments.Although the medical needles for percutaneous intervention technology appear to be mature,biomimetic solutions become popular to further facilitate the performance of the medical needles.In this paper,we review the current state of bio-inspired medical needle designs for percutaneous interventions,including a variety of biomimetic mechanisms and insertion strategies.Existing and experimental designs of biomimetic medical needles are classified into five groups with respect to the applications,while their characteristics are identified and discussed.Such classification and discussion will not only provide technical insights into previous studies but also identify undiscovered directions for future research.

关键词： Bio-inspired needle Biopsy needle Steerable needle

A survey of the development of biomimetic intelligence and robotics

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Biomimetic intelligence & robotics 2021年第1期1卷 1-12页

作者： Jiankun Wang Weinan Chen Xiao Xiao Yangxin Xu Chenming Li Xiao Jia Max Q-H.Meng Department of Electronic and Electrical Engineering Southern University of Science and TechnologyShenzhenChina Department of Electronic Engineering The Chinese University of Hong KongShatin N.T.Hong Kong SARChina shenzhen Research Institute of the Chinese University of Hong Kong ShenzhenChina

Biomimetics is the development of novel theories and technologies by emulating the models and systems of nature.The transfer of function from biological science into engineering promotes emerging research areas across many disparate disciplines.Recently,advances in biomimetic intelligence and robotics have gained great popularity.Biomimetic robotics are designed with biological characteristics and functions to be applied in different scenarios,such as humanoid robot in the home environment,quadruped robot in the field,and bird-like flying robot in the sky.Biomimetic intelligence aims to solve many complex problems by studying the principles of biological systems,resulting in a series of efficient algorithms,such as the genetic algorithm and neural network.Biomimetic intelligence further facilitates the performance of biomimetic robotics,making it possible to be deployed in more and more practical applications.This survey introduces the development of biomimetic intelligence and biomimetic robotics.We survey different biomimetic robots,biomimetic sensors and sensing technologies,and popular biomimetic intelligence algorithms.The conclusion is drawn by discussing current challenges and future research directions.

关键词： Biomimetics robotics Biomimetic intelligence Biomimetic robotics

Multimodal Locomotion and Cargo Transportation of Magnetically Actuated Quadruped Soft Microrobots

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Cyborg and Bionic Systems 2022年第1期2022卷 12-21页

作者： Chenyang Huang Zhengyu Lai Xinyu Wu Tiantian Xu Guangdong Provincial key Lab of robotics and Intelligent System Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for SocietyShenzhen 518055China University of Chinese Academy of Sciences Beijing 100049China

Untethered microrobots have attracted extensive attention due to their potential for biomedical applications and micromanipulation at the small scale.Soft microrobots are of great research importance because of their highly deformable ability to achieve not only multiple locomotion mechanisms but also minimal invasion to the environment.However,the existing microrobots are still limited in their ability to locomote and cross obstacles in unstructured environments compared to conventional legged robots.Nature provides much inspiration for developing miniature robots.Here,we propose a bionic quadruped soft thin-film microrobot with a nonmagnetic soft body and 4 magnetic flexible legs.The quadruped soft microrobot can achieve multiple controllable locomotion modes in the external magnetic field.The experiment demonstrated the robot’s excellent obstacle-crossing ability by walking on the surface with steps and moving in the bottom of a stomach model with gullies.In particular,by controlling the conical angle of the external conical magnetic field,microbeads gripping,transportation,and release of the microrobot were demonstrated.In the future,the quadruped microrobot with excellent obstacle-crossing and gripping capabilities will be relevant for biomedical applications and micromanipulation.

关键词： robot obstacle steps

Strenuous exercise-tolerance stretchable dry electrodes for continuous multi-channel electrophysiological monitoring

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npj Flexible Electronics 2022年第1期6卷 745-753页

作者： Ruijie Xie Qingsong Li Lijun Teng Zhengshuai Cao Fei Han Qiong Tian Jing Sun Yang Zhao Mei Yu Dianpeng Qi Peizhi Guo Guanglin Li Fengwei Huo Zhiyuan Liu CAS key laboratory of Human-Machine intelligence-Synergy Systems Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences(CAS)Shenzhen 518055China The Institute of Flexible Electronics(IFE Future Technologies)Xiamen UniversityXiamen361005 FujianChina key laboratory of Flexible Electronics(KLOFE) School of Flexible Electronics(Future Technologies)Nanjing Tech University30 South Puzhu RoadNanjing 211816China Institute of Materials for Energy and Environment State Key Laboratory of Bio-fibers and Eco-textilesCollege of Materials Science and EngineeringQingdao UniversityQingdao 266071China MIIT key laboratory of Critical Materials Technology for New Energy Conversion and Storage School of Chemistry and Chemical EngineeringHarbin Institute of TechnologyHarbin 150001China

Electrophysiological monitoring under strenuous exercise by using stretchable dry electrodes is vital for healthcare monitoring,prosthetic control,human−machine interfaces and other biomedical applications.However,the existing dry electrodes are not applicable to the strenuous exercise situation that always involves both fast moving and profuse sweating.Herein,we present a nano-thick porous stretchable dry electrode system with high stretchability and water permeability.The system attaches conformably to the skin and stretches with it under Van der Waals forces even at sweating conditions,allowing the detection of electromyogram when moving with an acceleration of 10 g at a sweating rate of 2.8 mg cm^(−2) min^(−1).It is also capable of acquiring electrocardiogram and electroencephalogram signals.The strategy proposed would enable the biomedical studies and related applications with the requirement of stably recording electrophysiological signals under strenuous exercise scenarios.

关键词： acceleration recording enable