Mechatronics最新文献_第3页

Ultra-Local Sliding Mode Control with Control Barrier Functions: A Framework for Adaptive Cruise Control 具有控制障碍函数的超局部滑模控制：一种自适应巡航控制框架

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2026-01-01 Epub Date: 2025-11-20 DOI: 10.1016/j.mechatronics.2025.103430

Fernando Zolubas Preto , Bruno Augusto Angélico , Evandro Leonardo Silva Teixeira , João Francisco Justo

This work proposes a unification of safety-proven control laws with modeling-free approaches, with a primary focus on handling complex applications. The proposed control law is an Ultra-Local Sliding-Mode Control (ULSMC) with Control Barrier Function (CBF) that is a combination capable of ensuring safety and robustness using minimal phenomenological modeling. This approach is used to design an Adaptive Cruise Control (ACC) system that has successfully accomplished some of the most challenging Euro NCAP Tests in a Hardware-In-the-Loop platform, using a realistic vehicular simulator. Moreover, a cubic per part condition is developed on the time derivative of the CBF, allowing the CBF safety filter to dynamically arbitrate between prioritizing safety, performance, or safety-recoverability according to the safety level measured by the CBF function. In particular, safety-recoverability is verified through simulations of realistic hazardous scenarios caused by external vehicles on the road. Furthermore, a modified headway-time-based CBF is developed to address ACC operation under complete stop scenarios. The robustness of the ULSMC control is shown to be essential to ensure ACC performance requirements when adopting an almost modeling-free approach.

这项工作提出了安全证明的控制律与无建模方法的统一，主要关注处理复杂的应用程序。所提出的控制律是一种具有控制障碍函数（CBF）的超局部滑模控制（ULSMC），它是一种能够使用最小现象学建模确保安全性和鲁棒性的组合。该方法被用于自适应巡航控制（ACC）系统的设计，该系统已经成功地在硬件在环平台上完成了一些最具挑战性的欧洲NCAP测试，使用了逼真的车辆模拟器。此外，在CBF的时间导数上建立了每部分立方的条件，允许CBF安全过滤器根据CBF函数测量的安全级别动态地在优先安全、性能或安全可恢复性之间进行仲裁。特别是，通过模拟外部车辆在道路上造成的现实危险情景，验证了安全可恢复性。此外，开发了一种改进的基于进度时间的CBF，以解决完全停止情况下的ACC操作问题。当采用几乎无需建模的方法时，ULSMC控制的鲁棒性对于确保ACC性能要求至关重要。

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引用次数: 0

Reconfigurable hydrostatics: Toward versatile and efficient load-bearing robotics 可重构流体静力学：走向多功能和高效的承载机器人

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2026-01-01 Epub Date: 2025-10-23 DOI: 10.1016/j.mechatronics.2025.103420

Jeff Denis, Frédéric Laberge, Jean-Sébastien Plante, Alexandre Girard

Wearable and legged robot designers face multiple challenges when choosing actuation. Traditional fully actuated designs using electric motors are multifunctional but oversized and inefficient for bearing conservative loads and for being backdrivable. Alternatively, quasi-passive and underactuated designs reduce the amount of motorization and energy storage, but are often designed for specific tasks. Designers of versatile and stronger wearable robots will face these challenges unless future actuators become very torque-dense, backdrivable and efficient.

This paper explores a design paradigm for addressing this issue: reconfigurable hydrostatics. We show that a hydrostatic actuator can integrate a passive force mechanism and a sharing mechanism in the fluid domain and still be multifunctional. First, an analytical study compares the effect of these two mechanisms on the motorization requirements in the context of a load-bearing exoskeleton. Then, the hydrostatic concept integrating these two mechanisms using hydraulic components is presented. A case study analysis shows the mass/efficiency/inertia benefits of the concept over a fully actuated one. Then, experiments are conducted on robotic legs to demonstrate that the actuator concept can meet the expected performance in terms of force tracking, versatility, and efficiency under controlled conditions. The proof-of-concept can track the vertical ground reaction force (GRF) profiles of walking, running, squatting, and jumping, and the energy consumption is 4.8x lower for walking. The transient force behaviors due to switching from one leg to the other are also analyzed along with some mitigation to improve them.

可穿戴式和腿式机器人的设计者在选择驱动方式时面临着多重挑战。使用电动机的传统全驱动设计是多功能的，但在承受保守负载和反向驱动方面体积过大，效率低下。另外，准被动和欠驱动设计减少了机动化和能量存储的数量，但通常是为特定任务而设计的。除非未来的驱动器变得非常扭矩密集、可反向驱动和高效，否则多功能和更强大的可穿戴机器人的设计者将面临这些挑战。本文探讨了解决这个问题的设计范例：可重构流体静力学。研究表明，流体静压作动器可以将流体领域的被动受力机构和共享机构集成在一起，并且仍然具有多功能。首先，一项分析研究比较了这两种机制在承重外骨骼环境下对机动化要求的影响。然后，提出了利用液压元件将这两种机构结合起来的流体静力学概念。案例分析表明，与完全驱动的概念相比，该概念在质量/效率/惯性方面具有优势。然后，在机器人腿上进行了实验，验证了执行器概念在受控条件下的力跟踪、通用性和效率方面能够满足预期的性能。概念验证可以跟踪步行，跑步，蹲起和跳跃的垂直地面反作用力（GRF）曲线，并且步行的能量消耗降低4.8倍。还分析了从一条腿切换到另一条腿时的瞬态力行为，并提出了一些改进措施。

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引用次数: 0

Visual SLAM algorithm based on dynamic attribute recognition in dynamic scenes 基于动态场景动态属性识别的视觉SLAM算法

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2026-01-01 Epub Date: 2025-11-22 DOI: 10.1016/j.mechatronics.2025.103427

Jian Xiong , Longwei Fan , Dayong Yang , Pengwen Xiong , Jie Lu , Weisheng Zhong

Visual SLAM algorithms suffer from errors in dynamic scenes due to interference from dynamic objects, leading to significant degradation in system accuracy. Existing deep learning-based methods for removing feature points of dynamic objects focus solely on actively moving objects with prior information, neglecting the dynamic characteristics of passive objects. To address this issue, we propose the concept of dynamic attribute recognition based on active–passive relationships; starting from the correlation between objects, we determine the dynamic attributes of passive objects based on the dynamic attributes of active objects. Building upon this, we propose a visual SLAM algorithm based on dynamic attribute recognition. First, YOLO is employed for object detection to identify the semantic information of objects and obtain their positional information. Then, the Euclidean distance is used to determine the affiliation between active and passive objects. Specifically, if the active object is a person, the Euclidean distance between the passive object and the hand keypoints determines their affiliation. Simultaneously, the Lucas-Kanade optical flow method and RANSAC are used to further assist in determining the dynamic attributes of both active and passive objects. Finally, feature points within the regions occupied by active and passive objects identified as dynamic are either removed or their weights are reduced, relying on static feature points to achieve camera pose estimation. Experimental results demonstrate that our algorithm reduces both the Absolute Trajectory Error (ATE) and Relative Pose Error (RPE) by over 90% compared to the original ORB-SLAM2 on high-dynamic sequences of the TUM dataset. Compared to similar algorithms such as DS-SLAM and Dyna-SLAM, our method exhibits superior accuracy and robustness in dynamic scenes containing both active and passive objects, with the tracking thread processing each frame in an average of only 29.36 ms. Our approach significantly enhances both the accuracy and real-time performance of SLAM algorithms in dynamic scenes.

视觉SLAM算法在动态场景中会受到动态对象的干扰而产生误差，导致系统精度显著下降。现有的基于深度学习的动态物体特征点去除方法只关注具有先验信息的主动运动物体，而忽略了被动物体的动态特征。为了解决这一问题，我们提出了基于主-被动关系的动态属性识别概念；从对象之间的相关性出发，基于主动对象的动态属性确定被动对象的动态属性。在此基础上，提出了一种基于动态属性识别的视觉SLAM算法。首先，利用YOLO进行目标检测，识别目标的语义信息，获取目标的位置信息。然后，利用欧几里得距离来确定主动和被动物体之间的隶属关系。具体来说，如果主动对象是人，则被动对象与手关键点之间的欧几里得距离决定了它们的隶属关系。同时，利用Lucas-Kanade光流法和RANSAC进一步辅助确定主动式和被动式目标的动态属性。最后，将识别为动态的主动和被动物体所占区域内的特征点去除或降低其权重，依靠静态特征点实现相机姿态估计。实验结果表明，在TUM数据集的高动态序列上，与原始ORB-SLAM2相比，我们的算法将绝对轨迹误差（ATE）和相对姿态误差（RPE）降低了90%以上。与DS-SLAM和Dyna-SLAM等算法相比，该方法在包含主动和被动目标的动态场景中表现出更高的精度和鲁棒性，跟踪线程处理每帧的平均时间仅为29.36 ms。我们的方法显著提高了SLAM算法在动态场景中的精度和实时性。

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引用次数: 0

Design and multi-objective optimization of a novel robust command shaping technique for the tolerable level of residual vibration 一种新的残余振动可容忍水平鲁棒指令成形技术的设计与多目标优化

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2026-01-01 Epub Date: 2025-11-21 DOI: 10.1016/j.mechatronics.2025.103426

Ferhat Kaya , Caglar Conker

This manuscript addresses the problem of designing a robust input shaper capable of suppressing residual vibrations in flexible robotic and mechanical systems under modeling errors and parameter uncertainties, while also providing smooth reference commands.The proposed approach integrates Cycloid, Ramped Versine and Ramp (CPRVPR) functions with Zero Vibration (ZV, ZVD, and ZVDD) input shapers, optimizing their parameters using the Vibrating Particle System (VPS) Algorithm. Furthermore, the study proposes a novel multi-objective function that accounts for critical parameters of input shaping techniques in flexible robotic systems and the robustness constraints of Extra-Insensitive input shapers. The theoretical outcomes of the proposed command shaping approaches were experimentally validated through their application to a linear crane system. The effectiveness of the three proposed methods was demonstrated by comparing them against fifteen well-known input shaping techniques. The novel intelligent command shaping design was shown to effectively mitigate or eliminate residual vibrations in flexible systems, even under high levels of uncertainty.

本文解决了设计一个鲁棒输入整形器的问题，该整形器能够在建模误差和参数不确定的情况下抑制柔性机器人和机械系统中的残余振动，同时还提供平滑的参考命令。该方法将摆线、斜线和斜线（CPRVPR）函数与零振动（ZV、ZVD和ZVDD）输入形状器相结合，利用振动粒子系统（VPS）算法对其参数进行优化。此外，该研究提出了一个新的多目标函数，该函数考虑了柔性机器人系统中输入整形技术的关键参数和超不敏感输入整形器的鲁棒性约束。通过对线性起重机系统的实验验证了所提出的命令成形方法的理论结果。通过将这三种方法与15种知名的输入整形技术进行比较，证明了它们的有效性。研究表明，即使在高度不确定的情况下，这种新颖的智能指令整形设计也能有效地减轻或消除柔性系统中的残余振动。

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引用次数: 0

Learning feedforward with unmeasured performance variables: With application to a wirebonder 具有未测量性能变量的学习前馈：应用于焊丝机

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2026-01-01 Epub Date: 2025-10-28 DOI: 10.1016/j.mechatronics.2025.103422

Maurice Poot , Jorrit Sprik , Matthijs Teurlings , Wout Laarakkers , Dragan Kostić , Jim Portegies , Tom Oomen

Feedforward motion control for unmeasured performance variables at the point of interest is crucial for attaining high throughput and accuracy in motion systems. The aim of this paper is to develop a data-driven approach for feedforward tuning that addresses the true performance at the point of interest. The presented approach is a novel methodology that employs rational feedforward structures for performing flexible tasks with high accuracy, in conjunction with an sensor fusion for addressing the point-of-interest. In particular, the tracking error of the unmeasured performance variable is accurately estimated by combining acceleration measurements and encoder measurements. Simulation results show that optimizing for the estimated point-of-interest error achieves similar tracking performance as optimizing for the true point-of-interest error, indicating accurate sensor-fusion estimates for feedforward control. Experimental validation demonstrates that optimizing for the estimated point-of-interest error significantly reduces the estimated point-of-interest tracking error compared to minimizing the encoder error.

在感兴趣的点对未测量的性能变量进行前馈运动控制对于在运动系统中获得高吞吐量和准确性至关重要。本文的目的是开发一种数据驱动的前馈调优方法，以解决感兴趣点的真实性能。所提出的方法是一种新颖的方法，它采用合理的前馈结构来执行高精度的灵活任务，并结合传感器融合来解决感兴趣点。特别是结合加速度测量和编码器测量，准确估计了未测性能变量的跟踪误差。仿真结果表明，对估计兴趣点误差的优化与对真实兴趣点误差的优化获得了相似的跟踪性能，表明对前馈控制的传感器融合估计是准确的。实验验证表明，与最小化编码器误差相比，对估计的兴趣点误差进行优化可以显着降低估计的兴趣点跟踪误差。

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引用次数: 0

Data-driven pressure controller using proportional piezoelectric valves for soft pneumatic actuators 数据驱动的压力控制器采用比例压电阀的软气动执行器

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2026-01-01 Epub Date: 2025-11-22 DOI: 10.1016/j.mechatronics.2025.103428

A. Pawluchin , T.-L. Habich , T. Seel , I. Boblan

Pressure control forms the foundation for operating soft pneumatic actuators (SPAs). For effective motion or force control, however, the underlying pressure control must be both fast and accurate. This can be achieved either by placing the valve close to the actuator or by compensating for long pneumatic tubes through dynamic modeling. Tube compensation, however, is complex and difficult to implement, while direct valve mounting is often impractical because conventional proportional valves are large and heavy.

To overcome these limitations, a compact, custom-designed 3/3-valve unit (CVU) based on Festo’s VEAE piezoelectric valves is developed. The CVU supports pressures up to 6 bar, flow rates up to 70 l/min and control bandwidths exceeding 9 Hz. It is controlled using the presented data-driven approach, which eliminates the need for classical system identification and automatically adapts to different actuator volumes, resulting in high accuracy and simple deployment.

The control scheme employs a two-stage, data-driven architecture based on single-shot Gaussian process (GP) regression. First, the inverse static flow characteristics of each valve are modeled, compensating for valve-to-valve variability without manual mass-flow identification. Second, the CVU is adapted to the actuator’s state-dependent volume, improving accuracy and robustness to external disturbances. In both stages, only the pressure derivative is used, avoiding the need for additional flow sensors or external test benches and keeping the approach lightweight and low-cost. The CVU with the data-driven control method was validated on an antagonistic pneumatic arm with pneumatic artificial muscles (PAMs) and benchmarked against a manually tuned PID controller, a feedback-linearized controller based on analytical system inversion and a commercially available VEAB valve unit. Across all tests, the CVU with GP-based control achieved highly accurate pressure tracking and disturbance rejection. All hardware (CAD) and development code (m-code) are released as open source.

压力控制是操作软气动执行器（spa）的基础。然而，对于有效的运动或力控制，底层压力控制必须既快速又准确。这可以通过将阀门靠近执行器或通过动态建模补偿长气动管来实现。然而，管道补偿是复杂和难以实施的，而直接安装阀门通常是不切实际的，因为传统的比例阀又大又重。为了克服这些限制，基于Festo的VEAE压电阀开发了一种紧凑的定制设计的3/3阀单元（CVU）。CVU支持压力高达6bar，流量高达70l /min，控制带宽超过9hz。该系统采用数据驱动的方法进行控制，消除了传统系统识别的需要，并自动适应不同的执行器体积，从而实现高精度和简单的部署。该控制方案采用基于单次高斯过程（GP）回归的两阶段数据驱动架构。首先，对每个阀门的反向静态流量特性进行建模，补偿阀门间的可变性，而无需人工进行质量流量识别。其次，CVU适应于执行器的状态相关体积，提高了精度和对外部干扰的鲁棒性。在这两个阶段中，只使用压力导数，避免了额外的流量传感器或外部测试台的需要，并保持了该方法的轻量化和低成本。采用数据驱动控制方法的CVU在带有气动人工肌肉（pam）的拮抗气动臂上进行了验证，并与手动调谐PID控制器、基于解析系统反演的反馈线性化控制器和市售VEAB阀单元进行了基准测试。在所有测试中，基于gp控制的CVU实现了高精度的压力跟踪和干扰抑制。所有硬件（CAD）和开发代码（m-code）都是开源的。

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引用次数: 0

Fixed-time adaptive sliding mode momentum observer for external torque estimation of robotic manipulators 机械臂外转矩估计的定时自适应滑模动量观测器

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2026-01-01 Epub Date: 2025-11-12 DOI: 10.1016/j.mechatronics.2025.103429

Jiahua Ma , Wenxiang Deng , Wei Chen , Jian Hu , Jianyong Yao

This paper proposes a fixed-time adaptive sliding mode momentum observer (FTASMMO) to improve external torque estimation in robotic manipulators interacting with the environment, without the need for torque sensors, thus enabling effective collision detection. Specifically, the proposed observer integrates fixed-time stability with generalized momentum, ensuring that the estimation error of external torques remains fixed-time stable. An adaptive law is introduced to effectively handle time-varying external torques with unknown upper bounds, while reducing conservatism in gain selection. The observer also employs a smooth tanh function in place of a sign function to reduce estimation chattering and improve observation accuracy. Additionally, Lyapunov analysis is employed to demonstrate the fixed-time stability of the observer. Simulation and experiments with a 7-degree-of-freedom collaborative robot demonstrate that the proposed observer significantly improves the speed and accuracy of torque estimation compared to existing methods.

本文提出了一种固定时间自适应滑模动量观测器（FTASMMO），以改进机器人与环境交互时的外部扭矩估计，而不需要扭矩传感器，从而实现有效的碰撞检测。具体来说，该观测器将定时稳定性与广义动量相结合，保证了外部力矩的估计误差保持定时稳定。引入一种自适应律，有效地处理带有未知上界的时变外部转矩，同时降低了增益选择的保守性。该观测器还采用平滑tanh函数代替符号函数，以减少估计抖振，提高观测精度。此外，采用李雅普诺夫分析来证明观测器的定时稳定性。对一个7自由度协作机器人的仿真和实验表明，与现有方法相比，该观测器显著提高了力矩估计的速度和精度。

引用次数: 0

Parameter identification algorithm for separated cable-driven parallel mechanisms via calibration error compensation 基于标定误差补偿的分离式缆索驱动并联机构参数辨识算法

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2025-12-01 Epub Date: 2025-10-22 DOI: 10.1016/j.mechatronics.2025.103421

Yanze Zhang, Yongnian Zhang, Jieyu Xian, Xingyu Lu, Zhiqiang Huang, Xiaochan Wang

For traditional Cable-Driven Parallel Robot (CDPR), changing the workspace is relatively difficult and requires reconfiguring the anchor points and outer frame. The main reason is that the frame-type configuration is often difficult to unfold and the anchor points are hard to identify. Additionally, since the anchor points are not connected by a fixed structure, the parameters can only be determined through manual measurement, which has limited accuracy. Therefore, the position values of the anchor points should be re-identified using appropriate calibration methods, particularly through the use of rapid automatic calibration methods. This paper proposes a rapid identification and calibration-error compensation method for anchor points of a separated cable-driven parallel robot operating in a non-structured environment. By calibration-error compensation, we refer to the simultaneous estimation and correction of anchor-point positions and calibration-reference errors, which reduces bias from imperfect calibration hardware and enhances identification robustness. To improve the motion accuracy of the moving platform, a static motion error identification model is established based on kinematics, and a least squares method is employed to fit the model and calculate the kinematic parameter positions. Additionally, since calibration plates are used for calibration, random errors may occur. Therefore, a hybrid optimization framework combining AHDBO and the least squares method is further proposed to address the local optimality problem caused by multi-anchor point error coupling. Experimental results showed that after parameter identification and error compensation, the average anchor point identification error was 3.225 mm, and the motion platform position error was 2.20 mm. These results confirm that the proposed parameter identification and compensation methods can effectively improve deployment precision in separated CDPR.

对于传统的缆索驱动并联机器人（CDPR）来说，改变工作空间比较困难，需要重新配置锚点和外框架。主要原因是框架型结构往往难以展开，锚点难以识别。此外，由于锚点之间没有固定结构连接，只能通过人工测量来确定参数，精度有限。因此，应使用适当的校准方法，特别是通过使用快速自动校准方法，重新确定锚点的位置值。提出了一种非结构环境下分离索驱动并联机器人锚点的快速识别与标定误差补偿方法。通过校准误差补偿，我们可以同时估计和修正锚点位置和校准参考误差，从而减少了校准硬件不完善带来的偏差，增强了识别的鲁棒性。为提高运动平台的运动精度，建立了基于运动学的静态运动误差辨识模型，采用最小二乘法对模型进行拟合，计算运动参数位置。此外，由于校正板用于校正，可能会出现随机误差。为此，进一步提出了AHDBO与最小二乘法相结合的混合优化框架，解决了多锚点误差耦合引起的局部最优性问题。实验结果表明，经过参数辨识和误差补偿后，平均锚点辨识误差为3.225 mm，运动平台位置误差为2.20 mm。结果表明，所提出的参数辨识与补偿方法能够有效提高分离式CDPR的部署精度。

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引用次数: 0

Snake robots: A state-of-the-art review on design, locomotion, control, and real-world applications 蛇形机器人：对设计、运动、控制和现实世界应用的最新评述

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2025-12-01 Epub Date: 2025-10-07 DOI: 10.1016/j.mechatronics.2025.103418

Syed Kumayl Raza Moosavi , Muhammad Hamza Zafar , Filippo Sanfilippo

Snake robots have emerged as a transformative class of bio-inspired robotic systems, offering unparallelled adaptability in navigating complex unstructured terrains. Their limbless design, inspired by biological snakes, enables efficient movement across diverse environments, including rough terrains, confined spaces, and hazardous conditions where traditional wheeled or legged robots struggle. This review provides a comprehensive analysis of the design and development of snake robots, covering their locomotion strategies, mechanical configurations, sensor integration, control schemas, and actuation mechanisms. The review further explores the evolution of mechanical structures from rigid, soft, and hybrid designs, emphasising advancements in actuation and sensor technologies in enhancing adaptability and navigation. Applications of snake robots extend across various domains, including search and rescue (SAR), industrial inspection, and exploration of extreme environments. Despite significant progress, challenges such as optimising energy efficiency, improving environmental perception, and achieving real-time adaptability remain open research areas. This review serves as a foundational reference for researchers and engineers working towards advancing the next generation of snake robots, paving the way for their integration into real-world applications.

蛇形机器人已经成为一种革命性的仿生机器人系统，在导航复杂的非结构化地形方面具有无与伦比的适应性。他们的无肢设计受到生物蛇的启发，能够在各种环境中高效移动，包括崎岖的地形，狭窄的空间，以及传统轮式或腿式机器人难以应对的危险条件。本文综述了蛇形机器人的设计和开发，包括它们的运动策略、机械结构、传感器集成、控制方案和驱动机制。这篇综述进一步探讨了机械结构从刚性、柔性和混合设计的演变，强调了驱动和传感器技术在增强适应性和导航方面的进步。蛇形机器人的应用范围广泛，包括搜索和救援（SAR）、工业检测和极端环境探索。尽管取得了重大进展，但诸如优化能源效率、改善环境感知和实现实时适应性等挑战仍然是开放的研究领域。这篇综述为致力于推进下一代蛇形机器人的研究人员和工程师提供了基础参考，为它们融入现实世界的应用铺平了道路。

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引用次数: 0

Autonomous exploration of mobile robot equipped with LiDAR for high-quality reconstruction in large-scale indoor environments 基于激光雷达的移动机器人自主探索，实现大尺度室内环境的高质量重建

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2025-12-01 Epub Date: 2025-09-26 DOI: 10.1016/j.mechatronics.2025.103409

Pin-Chu Shih , Yun-Chi Chiang , Jun-Jie Hu , Kuan-Ting Lin , Li-Chen Fu

High-quality 3D reconstruction is essential for applications such as autonomous driving, Augmented Reality (AR)/Virtual Reality (VR), and smart cities. Traditional methods using handheld sensors often result in incomplete and misaligned models. While autonomous exploration can improve these results, it often sacrifices quality for speed. This paper proposes a novel system for high-quality 3D reconstruction of large-scale indoor environments, leveraging a mobile robot equipped with a solid-state LiDAR mounted on a 2-degree-of-freedom (2-DOF) gimbal. The gimbal provides flexible scanning capabilities to overcome field-of-view (FoV) limitations of solid-state LiDARs. To address high-frequency, real-time quality evaluation during exploration, we introduce a new concept called guard-points, which guides the robot toward areas with insufficient point cloud density. These guard-points, alongside conventional frontier-based viewpoints, enable our planner to dynamically balance exploration and reconstruction quality. 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.

高质量的3D重建对于自动驾驶、增强现实(AR)/虚拟现实（VR）和智慧城市等应用至关重要。使用手持传感器的传统方法往往导致模型不完整和不对齐。虽然自主探索可以改善这些结果，但它往往为了速度而牺牲质量。本文提出了一种新型的高质量室内环境三维重建系统，该系统利用了一个安装在2自由度（2-DOF）框架上的固体激光雷达移动机器人。该框架提供了灵活的扫描能力，以克服固态激光雷达的视场（FoV）限制。为了解决勘探过程中高频、实时的质量评估问题，我们引入了一个名为“守护点”的新概念，该概念可以引导机器人前往点云密度不足的区域。这些守护点与传统的边界视角一起，使我们的规划者能够动态平衡勘探和重建质量。该系统不仅可以控制移动机器人前往重建质量不足的未知地点和区域，还可以实现高频、实时的探索路径规划。最后通过各种仿真和实际实验验证了系统的有效性。

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引用次数: 0