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SSRN 2024年

作者： Tang, Tianyi Li, Yunfei Huang, Manjuan Mei, Mingqi Wang, Zizhao Zha, Fusheng Sun, Lining Liu, Huicong School of Mechanical and Electrical Engineering Jiangsu Provincial Key Laboratory of Advanced Robotics Soochow University Suzhou215123 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China

Ocean wave energy is a highly anticipated renewable energy source. However, due to the ultra-low frequency and random characteristics of ocean waves, efficient and high-power energy harvesting has been a great challenge. By ingeniously leveraging the phenomenon of sudden magnetic-torque variation in orthogonal magnetic fields, this paper proposes an innovative Mag-Boost mechanism, which is capable of converting ultra-low excitation below 1Hz to high-frequency oscillations of power-magnet more than 50Hz without direct contact. The energy conversion efficiency of this mechanism can be as high as 89.3%. By integrating four Mag-boost units into a circular array, a high-power wave energy harvester (WEH) with ultra-low frequency response capabilities has been proposed. At a frequency of 1Hz and an inclination angle of 30°, the WEH demonstrated a high output performance with power of 1.79W and power density of 1.88kW/m³, which is an order of magnitude higher than those of the previous reported ones. During the off-shore test at Yellow Sea, the WEH reached the peak open-circuit voltage of 10V, ensuring completely independent and stable power supply for wireless temperature and humidity sensors. Furthermore, the Mag-Boost mechanism also shows considerable potential for harvesting other forms of low-frequency environmental energy, including wind, vibration, and human kinetic energy. © 2024, The Authors. All rights reserved.

关键词： Water waves

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Improved Efficiency of Weakly Coupled Wireless High-Power Transfer Systems by Loss-Separation Strategy

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International Journal of Circuit Theory and Applications 2025年第0期

作者： The Nguyen, Hoach Al-Sumaiti, Ameena Saad Alhassan, Ahmad Bala Do, Ton Duc Smart OR Lab Advanced Power and Energy Center Department of Electrical Engineering Khalifa University Abu Dhabi United Arab Emirates Department of Robotics and Mechatronics School of Engineering and Digital Sciences Nazarbayev University Astana Kazakhstan

In the equivalent T-model of the loosely coupled transformers, the small mutual inductance can lead to higher conducting currents, which cause high losses in the primary circuit and significantly reduce the overall transfer efficiency under weak-coupling states. To overcome this challenge, this paper proposes a strategy to separate the primary loss components from the weak-coupling stage. In the proposed strategy, a gyrator in the form of a double-resonance T-block is added just before the weak-coupling stage to improve the overall efficiency. Then, the strategy is realized by various topologies such as compensating circuits, added coils, isolated transformers, and integrated-/split- inductors/coils. Also, the optimized designs and component selection for resonance and the mathematical derivation for optimal load resistances were investigated. ANSYS comparative analyses of the topologies are presented by considering practical aspects, including component designs, power flows, transfer efficiency, resonance frequency shifting, and optimal loads. Finally, the analyses were validated using the fabricated experimental setups and demonstrated an efficiency improvement of about 5% for a case with a coupling factor of 0.1. The proposed strategy offers suggestions for industrial designs of high-power wireless battery charging systems using resonant inductive coils. © 2025 John Wiley & Sons Ltd.

关键词： Inductive power transmission

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SwarmPRM: Probabilistic Roadmap Motion Planning for Large-Scale Swarm Robotic Systems

SwarmPRM: Probabilistic Roadmap Motion Planning for Large-Sc...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Yunze Hu Xuru Yang Kangjie Zhou Qinghang Liu Kang Ding Han Gao Pingping Zhu Chang Liu Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing China Department of Computer Sciences and Electrical Engineering (CSEE) Marshall University Huntington WV USA

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Large-scale swarm robotic systems consisting of numerous cooperative agents show considerable promise for performing autonomous tasks across various sectors. Nonetheless, traditional motion planning approaches often face a trade-off between scalability and solution quality due to the exponential growth of the joint state space of robots. In response, this work proposes SwarmPRM, a hierarchical, scalable, computationally efficient, and risk-aware sampling-based motion planning approach for large-scale swarm robots. SwarmPRM utilizes a Gaussian Mixture Model (GMM) to represent the swarm’s macroscopic state and constructs a Probabilistic Roadmap in Gaussian space, referred to as the Gaussian roadmap, to generate a transport trajectory of GMM. This trajectory is then followed by each robot at the microscopic stage. To enhance trajectory safety, SwarmPRM incorporates the conditional value-at-risk (CVaR) in the collision checking process to impart the property of risk awareness to the constructed Gaussian roadmap. SwarmPRM then crafts a linear programming formulation to compute the optimal GMM transport trajectory within this roadmap. Extensive simulations demonstrate that SwarmPRM outperforms state-of-the-art methods in computational efficiency, scalability, and trajectory quality while offering the capability to adjust the risk tolerance of generated trajectories.

关键词： Scalability Simulation Swarm robotics Probabilistic logic Linear programming Trajectory Planning Computational efficiency Safety Collision avoidance

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Multi-sensor Calibration System for Mobile Robots 7

Multi-sensor Calibration System for Mobile Robots

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7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023

作者： Wu, Wei Liu, Chang Cao, Wenhan Chen, Chao Li, Hongbo Li, Shengbo Eben The School of Vehicle and Mobility Tsinghua University Beijing100084 China The Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing100871 China The Robot R&D Department Geekplus Corp. Beijing100107 China

ISBN: (纸本)9798350340488

Multi-sensor calibration is crucial for mobile robots, especially in logistics and warehouse environments. While calibration techniques exist for individual sensors, industry-level calibration of the multiple sensors on mobile robots covering the entire operational life cycle is rarely explored. To bridge the gap, we present a fast, accurate, and scalable calibration system supporting both manufacturing and operation phases for mobile robots with diverse sensors like odometers, IMUs, LiDARs, and cameras. Specifically, we propose an online yaw angle estimation approach for IMU by fusing odometer data as compensation. Additionally, we pioneer an approach to calibrate 2D LiDAR using surrounding objects' reflectance strength as the calibration metric in the manufacturing phase calibration, and the iterative closest point method for refinements during operation phase calibration. Furthermore, we develop a least squares formulation to calibrate cameras' intrinsic and extrinsic parameters, achieving rapid convergence. The system has been used by Geekplus across factories worldwide including Asia, Europe, America, and Oceania, successfully calibrating and deploying over 30,000 mobile robots. © 2023 IEEE.

关键词： Logistics Mobile Robots Multi-sensor Calibration Warehouse Applications

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Parameter Design of Digital P-PI Controller for Motor Positioning Systems Using Limited Pole Placement Method

Parameter Design of Digital P-PI Controller for Motor Positi...

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Annual Conference of Industrial Electronics Society

作者： Yoshiyuki Urakawa Ngamlamai Sirichai Robotics Department Advanced Engineering Faculty Nippon Institute of Technology Saitama Japan Mechanical System Engineering Major Graduated School Nippon Institute of Technology Saitama Japan

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

Positioning systems with motors are widely used in industrial use. Many production systems, mechatronics systems or industrial robots use high speed and high precision positioning systems with motors. Generally, the controllers of the positioning systems are proportional-to-proportional-integral (P-PI) controllers. They are often used because they have small overshoots and easy to tune. However, it needs fine-tunings to make settling motions smooth. There may be two reasons why the fine-tunings are needed for P-PI controllers. One is the pole assignment constraint of P-PI controller. Three poles of the P-PI control systems for motor positioning cannot be assigned freely. One of the three poles always stay at a slow position. Another reason is the digital delay when the P-PI controllers are applied to the practical systems. The digital system with the delay becomes vibrational because of the phase delay of the calculation time. It makes the overshoot of the trajectory. In this paper, the influences and solutions of the pole assignment constraint and the digital delay are shown. The pole assignment constraint limits the performance of the closed loop. The feedforward controller is shown to be the solution of this constraint. The digital delay makes the overshoot, but it can be corrected by the limited pole placement (LPP) method proposed by the author. It enables accurate pole-zero assignment without overshoots under the conditions of the digital delay.

关键词： Industrial electronics Production systems Accuracy Mechatronics Motors Industrial robots Delays Trajectory Feedforward systems Oscillators

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Partial Feedback Linearized RISE Controller for Active Flutter Suppression

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IFAC-PapersOnLine 2022年第22期55卷 159-164页

作者： Balraj Sharma Pooja Agrawal Ajay Misra Dept of Aerospace Engineering Defence Institute of Advanced Technology Pune India School of Robotics Defence Institute of Advanced Technology Pune India

In this paper, Robust Integral of Sign of Error (RISE) based partial feedback linearized controller for active flutter suppression (AFS) of a two dimensional aerofoil is proposed. The aeroelastic system has two degrees of freedom i.e. pitch and plunge. To design the controller, linearized pitch dynamics of the aerofoil is considered. A significant feature of the proposed controller is that it does not need an accurate model of the plant as well as any knowledge of external disturbance or parametric uncertainty. Zero dynamics stability and closed loop stability of the overall system have been established. Simulations prove the robustness and efficacy of the designed controller against variation in free stream velocity, parametric uncertainty and external disturbances as compared to existing designs. Results prove that the designed controller has increased the flutter boundary by 48% more than critical flutter speed.

关键词： Active flutter suppression feedback linearization RISE parametric variation lyapunov stability external disturbance zero dynamics

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Target Defense with Multiple Defenders and an Agile Attacker via Residual Policy Learning

arXiv

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arXiv 2025年

作者： Tao, Jiyue Shen, Tongsheng Zhao, Dexin Zhang, Feitian Robotics and Control Laboratory Department of Advanced Manufacturing and Robotics College of Engineering and the State Key Laboratory of Turbulence and Complex Systems Peking University Beijing100871 China National Innovation Institute of Defense Technology Beijing100071 China

The target defense problem involves intercepting an attacker before it reaches a designated target region using one or more defenders. This letter focuses on a particularly challenging scenario in which the attacker is more agile than the defenders, significantly increasing the difficulty of effective interception. To address this challenge, we propose a novel residual policy framework that integrates deep reinforcement learning (DRL) with the force-based Boids model. In this framework, the Boids model serves as a baseline policy, while DRL learns a residual policy to refine and optimize the defenders’ actions. Simulation experiments demonstrate that the proposed method consistently outperforms traditional interception policies, whether learned via vanilla DRL or fine-tuned from force-based methods. Moreover, the learned policy exhibits strong scalability and adaptability, effectively handling scenarios with varying numbers of defenders and attackers with different agility levels. Copyright © 2025, The Authors. All rights reserved.

关键词： Adversarial machine learning

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CTE-MLO: Continuous-Time and Efficient Multi-LiDAR Odometry With Localizability-Aware Point Cloud Sampling

IEEE Transactions on Field Robotics

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IEEE Transactions on Field robotics 2025年 2卷 165-187页

作者： Hongming Shen Zhenyu Wu Yulin Hui Wei Wang Qiyang Lyu Tianchen Deng Yeqing Zhu Bailing Tian Danwei Wang Centre for Advanced Robotics Technology Innovation (CARTIN) Nanyang Technological University Nanyang Avenue Singapore School of Electrical and Information Engineering Tianjin University Tianjin China School of Electrical and Electronic Engineering Nanyang Technological University Nanyang Avenue Singapore

In recent years, LiDAR-based localization and mapping methods have achieved significant progress, thanks to their reliable and real-time localization capability. Considering that single LiDAR odometry often faces hardware failures and degeneracy in practical scenarios, multi-LiDAR odometry (MLO), as an emerging technology, is studied to enhance the performance of LiDAR-based localization and mapping systems. However, MLO can suffer from high computational complexity introduced by dense point clouds that are fused from multiple LiDARs, and the continuous-time measurement characteristic is constantly neglected by existing LiDAR odometry. This motivates us to develop a continuous-time and efficient MLO (CTE-MLO), which can achieve accurate and real-time estimation using multi-LiDAR measurements through a continuous-time perspective. In this article, the Gaussian process estimation is naturally combined with the Kalman filter, which enables each LiDAR point in a point stream to query the corresponding continuous-time trajectory using its time instants. A decentralized multi-LiDAR synchronization scheme is also devised to combine points from separate LiDARs into a single point cloud without the primary LiDAR assignment. Moreover, with the aim of improving the real-time performance of MLO without sacrificing robustness, a point cloud sampling strategy is designed with the consideration of localizability. To this end, CTE-MLO integrates synchronization, localizability-aware sampling, continuous-time estimation, and voxel map management within a Kalman filter framework, which can achieve high accuracy and robust continuous-time estimation within only a few linear iterations. The effectiveness of the proposed method is demonstrated through various scenarios, including public datasets and real-world applications. Exhaustive benchmarks on public datasets show that CTE-MLO is demonstratively competitive compared to other state-of-the-art (SOTA) methods in accuracy, robustness,

关键词： Point cloud compression Location awareness Laser radar Accuracy Simultaneous localization and mapping Real-time systems Robustness Odometry Synchronization Kalman filters

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Trajectory Planning Towards Water-Air Trans-Media Motion for Robotic Dolphin

Trajectory Planning Towards Water-Air Trans-Media Motion for...

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2024 China Automation Congress, CAC 2024

作者： Xiong, Yan Zhang, Pengfei Chen, Di Yu, Junzhi State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing100871 China Shandong Nuclear Power Company LTD Yantai265116 China School of Intelligence Science and Technology University of Science and Technology Beijing Beijing100083 China

ISBN: (纸本)9798350368604

Water-air trans-media navigators have multi-media motion modes, breaking through the limitation that traditional robots can only operate in a single medium. Autonomous navigation is an indispensable component of the process of trans-media motion. Most of the current work has only completed the development and testing of prototypes, and the problem of task-oriented motion planning and control needs to be solved. In this paper, a safe and efficient hierarchical approach is proposed. First, a novel rapidly exploring random tree-based algorithm is proposed to search for a suitable path. Then, by fixing bound waypoints, the time-optimization trajectory is planned. Finally, the trajectory tracker is designed based on nonlinear model predictive control (NMPC). Simulation experiments numerically validate the proposed method, offering some new insights for further trans-media motions. © 2024 IEEE.

关键词： Trajectories

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A Novel Approximation for the Spring Loaded Inverted Pendulum Model of Locomotion

A Novel Approximation for the Spring Loaded Inverted Pendulu...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Ali U. Kilic David J. Braun Department of Mechanical Engineering Advanced Robotics and Control Laboratory Center for Rehabilitation Engineering and Assistive Technology Vanderbilt University Nashville Tennessee USA

The Spring-Loaded Inverted Pendulum (SLIP) is one of the simplest models of robot locomotion. SLIP is commonly used to predict the center of mass motion and derive simple control laws for stable locomotion. However, the SLIP model is not integrable, which means that no closed-form relation can be derived to understand how the design and control parameters of the SLIP model affect stable locomotion. There exist a number of different analytical approximations to the SLIP model when considering small step lengths and symmetric steps. In this paper, we present a novel approximation to the SLIP model without relying on the small step length and the symmetric step assumption. The model was found to accurately predict the stability of the SLIP model for large and asymmetric steps and was used to design a controller to stabilize the SLIP model in a couple of steps.

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