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arXiv 2025年

作者： Yue, Lu Zhou, Dongliang Xie, Liang Yin, Erwei Zhang, Feitian Department of Advanced Manufacturing and Robotics the State Key Laboratory of Turbulence and Complex Systems College of Engineering Peking University Beijing100871 China Defense Innovation Institute Academy of Military Sciences Beijing100071 China Tianjin Artificial Intelligence Innovation Center Tianjin300450 China Department of Computer Science Harbin Institute of Technology Shenzhen Xili University Town Shenzhen518055 China

Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires agents to navigate unknown, continuous spaces based on natural language instructions. Compared to discrete settings, VLN-CE poses two core perception challenges. First, the absence of predefined observation points leads to heterogeneous visual memories and weakened global spatial correlations. Second, cumulative reconstruction errors in three-dimensional scenes introduce structural noise, impairing local feature perception. To address these challenges, this paper proposes ST-Booster, an iterative spatiotemporal booster that enhances navigation performance through multi-granularity perception and instruction-aware reasoning. ST-Booster consists of three key modules — Hierarchical SpatioTemporal Encoding (HSTE), Multi-Granularity Aligned Fusion (MGAF), and Value-Guided Waypoint Generation (VGWG). HSTE encodes long-term global memory using topological graphs and captures short-term local details via grid maps. MGAF aligns these dual-map representations with instructions through geometry-aware knowledge fusion. The resulting representations are iteratively refined through pretraining tasks. During reasoning, VGWG generates Guided Attention Heatmaps (GAHs) to explicitly model environment-instruction relevance and optimize waypoint selection. Extensive comparative experiments and performance analyses are conducted, demonstrating that ST-Booster outperforms existing state-of-the-art methods, particularly in complex, disturbance-prone environments. Copyright © 2025, The Authors. All rights reserved.

关键词： Topology

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Adaptive-LIO: Enhancing Robustness and Precision through Environmental Adaptation in LiDAR Inertial Odometry

arXiv

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arXiv 2025年

作者： Zhao, Chengwei Hu, Kun Xu, Jie Zhao, Lijun Han, Baiwen Wu, Kaidi Tian, Maoshan Yuan, Shenghai The State Key Laboratory of Robotics and Systems Harbin Institute of Technology HeiLongJiang Harbin150001 China Hangzhou Qisheng Intelligent Techology Co. Ltd. 4083 Jianshe Fourth Road Zhejiang Hangzhou311217 China The School of Mechatronic Engineering China University of Mining and Technology JiangSu Xuzhou221116 China The School of Mechanical and Electrical Engineering University of Electronic Science And Technology Sichuan Chengdu611731 China The School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue 639798 Singapore

The emerging Internet of Things (IoT) applications, such as driverless cars, have a growing demand for high-precision positioning and navigation. Nowadays, LiDAR inertial odometry becomes increasingly prevalent in robotics and autonomous driving. However, many current SLAM systems lack sufficient adaptability to various scenarios. Challenges include decreased point cloud accuracy with longer frame intervals under the constant velocity assumption, coupling of erroneous IMU information when IMU saturation occurs, and decreased localization accuracy due to the use of fixed-resolution maps during indoor-outdoor scene transitions. To address these issues, we propose a loosely coupled adaptive LiDAR-Inertial-Odometry named Adaptive-LIO, which incorporates adaptive segmentation to enhance mapping accuracy, adapts motion modality through IMU saturation and fault detection, and adjusts map resolution adaptively using multi-resolution voxel maps based on the distance from the LiDAR center. Our proposed method has been tested in various challenging scenarios, demonstrating the effectiveness of the improvements we introduce. The code is open-source on GitHub: Adaptive-LIO. © 2025, CC BY.

关键词： SLAM robotics

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Fuzzy behavior integration and action fusion for robotic excavation

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 1996年第3期43卷 395-402页

作者： Shi, XB Lever, PJA Wang, FY Advanced Mining Systems Laboratory and the Robotics and Automation Laboratory University of Arizona Tucson Tucson AZ USA Department of Mining and Geological Engineering University of Arizona Tucson Tucson AZ USA Robotics and Automation Laboratory and the Department of Systems and Industrial Engineering University of Arizona Tucson Tucson AZ USA

This paper discusses control behavior integration and bucket action fusion for excavation control of a robotic front-end-loader type machine, To utilize the experience and expertise from skilled human operators, a fuzzy-logic based control approach is developed, A hierarchical excavation control architecture decomposes excavation goals to tasks, then tasks to behaviors, and finally behaviors to actions, The excavation actions are primitive and can be executed directly by an excavation machine, Finite state machines are used to specify the coordination and integration of behaviors for task execution and actions for behavior implementation, A simple strategy for action fusion is proposed based on fuzzy logic reasoning and the COA defuzzification method. Finally, laboratory experiments are conducted using a PUMA 560 robot arm and a Zebra force/torque sensor in a simulated rock excavation environment. Experimental results indicate that the proposed approach in this paper has led to more efficient task execution than our previous approach.

关键词： Robot kinematics Humans Laboratories robotics and automation Automatic control Robot sensing systems Geology Control system synthesis Fuzzy control Robot control

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Multi-agent Gaussian Process Motion Planning via Probabilistic Inference

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IFAC-PapersOnLine 2018年第22期51卷 160-165页

作者： Petrovi, Luka Markovi, Ivan Seder, Marija University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Autonomous Systems and Mobile Robotics Croatia

This paper deals with motion planning for multiple agents by representing the problem as a simultaneous optimization of every agent's trajectory. Each trajectory is considered as a sample from a one-dimensional continuous-time Gaussian process (GP) generated by a linear time-varying stochastic differential equation driven by white noise. By formulating the planning problem as probabilistic inference on a factor graph, the structure of the pertaining GP can be exploited to find the solution efficiently using numerical optimization. In contrast to planning each agent's trajectory individually, where only the current poses of other agents are taken into account, we propose simultaneous planning of multiple trajectories that works in a predictive manner. It takes into account the information about each agent's whereabouts at every future time instant, since full trajectories of each agent are found jointly during a single optimization procedure. We compare the proposed method to an individual trajectory planning approach, demonstrating significant improvement in both success rate and computational efficiency. © 2018

关键词： Motion planning Computational efficiency Continuous time systems Differential equations Gaussian distribution Gaussian noise (electronic) Multi agent systems One dimensional Optimization Stochastic systems Trajectories White noise Factor graphs Numerical optimizations Optimization procedures Probabilistic inference Simultaneous optimization Stochastic differential equations Trajectory optimization Trajectory Planning

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Kinematic modeling and analysis of novel eight-wheel lunar rover

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Journal of Harbin Institute of Technology(New Series) 2009年第6期16卷 751-755页

作者：高海波张朋邓宗全胡明 State Key Laboratory of Robotics and Systems School of Mechatronic Engineering Harbin Institute of Technology

A new kind of eight-wheel lunar rover is developed, which is a complex closed-chain system and has good capabilities of climbing slope, surmounting obstacles and adapting to uneven terrain. In this paper, the mechanical structure of the novel eight-wheel lunar rover is introduced, forward and inverse kinematic models of the rover are established according to the closed-chain coordinate transformation and instantaneous coincidence coordinate. Based on structural characteristics, its kinetic characteristics are analyzed. Wheel slippages are separated and calculated, and a method for closed-loop control modification using wheel slip estimation during the model establishment is proposed. The results can be applied to the motion control of lunar rover.

关键词： kinematic modeling locomotion system eight-wheel lunar rover lunar rover

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Corretions to “An Automatic Navigation Framework for Magnetic Fish-Like Millirobot in Uncertain Dynamic Environments”

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IEEE robotics and Automation Letters 2025年第4期10卷 3875-3875页

作者： Chenyao Tian Xinjian Fan Jingzhi Jia Zhan Yang Hui Xie State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China School of Mechanical and Electrical Engineering Soochow University Suzhou China

The first author's name was misspelled as “Chengyao Tian” in [1], containing an extraneous “g”. The correct spelling is “Chenyao Tian”.

关键词： Navigation

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Hybrid Robotic Arm for Autonomous Aerial Refueling

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Chinese Journal of Mechanical engineering 2024年第6期37卷 429-440页

作者： Kaixuan Li Gangfeng Liu Yongsheng Gao Jie Zhao State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin 150080China School of Mechatronics Engineering Harbin 150080China

Autonomous aerial refueling technology is gaining increasing attention to enhance aircraft combat *** research on autonomous refueling focuses mainly on flight control laws,with little attention to the automation of refueling *** leads to high demands on control law performance and navigation accuracy,making it difficult to ensure *** address this,we propose a robotic arm system capable of automatic docking during the flexible aerial refueling *** system uses a conical kinematic space configuration,offering enhanced stability and impact *** frame-type structure achieves a lightweight ***,we establish a single-objective optimization model for the connecting rod dimensions and apply a genetic algorithm(GA)for their *** also propose a trajectory-fitting calibration theory based on the robotic arm's special configuration and complete its movement accuracy calibration using a laser *** calibration method reduces the robotic arm's motion error by 71%,achieving an absolute positioning accuracy better than 3.5 mm,which meets the requirements for autonomous aerial *** summary,this research presents a hybrid robotic arm that meets automatic docking requirements,offering a new approach to autonomous aerial refueling.

关键词： Autonomous aerial refueling Conical kinematic space configuration Optimization of structural design Calibration method

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A colorimetric-bionic sensor for multimodal molecular sensing using hierarchical metamaterials

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Device 2025年第5期3卷

作者： Geng, Wenhui Zhou, Ying Huang, Kang Ying, Yibin Xie, Lijuan College of Biosystems Engineering and Food Science Zhejiang University 866 Yuhangtang Road Hangzhou 310058 China The National Key Laboratory of Agricultural Equipment Technology Beijing 100083 China Zhejiang Key Laboratory of Intelligent Sensing and Robotics for Agriculture Hangzhou 310058 China Hangzhou Customs Technology Center 398 Jianshe San Road Xiaoshan District Hangzhou City China Department of Biological Systems Engineering Washington State University Pullman 99164 WA United States

Metamaterials can enhance a local electric field for molecular sensing. However, the difficulty in specifically recognizing target molecules and integrating multiple functionalities restricts their development. Here, we present a hierarchical metamaterial-based colorimetric-bionic sensor (HMm-CBs) using a layer-by-layer assembly method for multimodal molecular sensing. The CBs layers offer molecular recognition ability by enabling the specific perception of analytes, and the HMm layers provide coupling of vibrations between analyte molecules at the terahertz (THz) frequency. The HMm-CBs have broadband adaptability in controlling electromagnetic waves from optical to THz frequency. As a proof of principle, we designed a sensor for analyzing tetracycline hydrochlorides (TCHs). The sensor, in conjunction with a back propagation neural network (BPNN), identifies four types of TCHs. As a demonstration, a multichannel indicator is created for real-time monitoring of shrimp freshness and volatile metabolites. © 2025 The Author(s)

关键词： antibiotics carbon nanotubes chemometric algorithms colorimetric sensor array DTI-3: Develop metamaterials

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Multidirectional 3D printed functionally graded modular joint actuated by TCPFL muscles for soft robots

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Bio-Design and Manufacturing 2019年第4期2卷 256-268页

作者： Armita Hamidi Yara Almubarak Yonas Tadesse Humanoid Bio-robotics and Smart Systems(HBS)LaboratoryMechanical Engineering DepartmentThe University of Texas at DallasRichardsonTX 75080USA

Highly deformable bodies are essential for numerous types of applications in all sorts of environments. Joint-like structures comprising a ball and socket joint have many degrees of freedom that allow mobility of many biomimetic structures. Recently, soft robots are favored over rigid structures for their highly compliant material, high-deformation properties at low forces, and ability to operate in di fficult environments. However, it is still challenging to fabricate complex designs that satisfy application constraints due to the combined e ffects of material properties, actuation method, and structural geometry on the performance of the soft robot. Therefore, a combination of a rigid joint and a soft body can help achieve modular robots with fully functional body morphology. Yet, the fabrication of soft parts requires extensive molding for complex shapes, which comprises several processes and can be time-consuming. In addition, molded connections between extremely soft materials and hard materials can be critical failing points. In this paper, we present a functionally graded 3D-printed joint-like structure actuated by novel contractile actuators. Functionally graded materials (FGMs) via 3D printing allow for extensive material property enhancement and control which warrant tunable functionalities of the system. The 3D-printed structure is made of 3 rigid ball and socket joints connected in series and actuated by integrating twisted and coiled polymer fishing line ( TCPFL) actuators, which are con fined in the FGM accordion-shaped channels. The implementation of the untethered T CPFL actuation system can be highly bene ficial for deployment in environments that require low vibrations and silent actuation. The fishing line TCP actuators produce an actuation strain up to 40% and bend the joint up to 40° in any direction. The T CPFL can be actuated individually or as a group to control the bending trajectory of the modular joint, which is bene ficial when deployed i

关键词： Functionally graded 3D-printed Joint Multidirectional Fishing line TCP

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MOTION ESTIMATION OF 3-D OBJECTS USING MULTISENSOR DATA FUSION

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JOURNAL OF ROBOTIC systems 1990年第3期7卷 419-443页

作者： LUO, RC YANG, WS Robotics and Intelligent Systems Laboratory Electrical and Computer Engineering North Carloina State University Raleigh NC 27695–7911

This article presents an approach to estimate the general 3-D motion of a polyhedral object using multiple sensor data some of which may not provide sufficient information for the estimation of object motion. Motion can be estimated continuously from each sensor through the analysis of the instantaneous state of an object. The instantaneous state of an object is specified by the rotation, which is defined by a rotation axis and rotation angle, and the displacement of the center of rotation. We have introduced a method based on Moore-Penrose pseudoinverse theory to estimate the instantaneous state of an object, and a linear feedback estimation algorithm to approach the motion estimation. The motion estimated from each sensor is fused to provide more accurate and reliable information about the motion of an unknown object. The techniques of multisensor data fusion can be categorized into three methods: averaging, decision, and guiding. We present a fusion algorithm which combines averaging and decision. With the assumption that the motion is smooth, our approach can handle the data sequences from multiple sensors with different sampling times. We can also predict the next immediate object position and its motion. The simulation results show our proposed approach is advantageous in terms of accuracy, speed, and versatility.

关键词： Robots, Industrial

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