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Autonomous navigation of a tracked unmanned ground vehicle*

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IFAC-PapersOnLine 2022年第14期55卷 120-125页

作者： Marija Seder Anđela Jurić Ana Šelek Filip Marić Marija Lovrić Ivan Petrović University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Laboratory for Autonomous Systems and Mobile Robotics (LAMOR) Zagreb Croatia University of Zagreb Croatian Military Academy Dr. Franjo Tuđman Zagreb Croatia

This work proposes a complete autonomous navigation system for a tracked vehicle. The system enables a complete autonomous execution of waypoint and patrolling tasks selected by the user. It also enables user-vehicle shared autonomy, switching between the user teleoperation and the vehicle autonomous operation. Our navigation system uses the model predictive control scheme based on a navigation function. We propose the navigation function which takes into account changing environments, any-shape footprint, and non-holonomic motion of the tracked vehicle. Besides the waypoint and patrolling tasks, we implemented a fail-safe scenario in case of the user-vehicle communication loss, in which the vehicle returns autonomously to the previously visited goal where the communication was stable. The efficiency of the proposed system is validated by experimental results on the Komodo tracked vehicle.

关键词： Robot navigation path planning obstacle detection avoidance motion control map building

CapsuleBot: A Novel Hybrid Aerial-Ground Bi-Copter Robot with Two Actuated-Wheel-Rotors

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arXiv 2023年

作者： Zheng, Zhi Cai, Qifeng Wang, Jin Xu, Xinhang Cao, Muqing Yu, Huan Li, Jihao Meng, Jun Lu, Guodong State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310027 China Robotics Institute of Zhejiang University Zhejiang University Hangzhou310027 China Robotics Research Center of Yuyao City Ningbo315400 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore Robotics Institute Carnegie Mellon University 5000 Forbes Avenue Pittsburgh15217 United States Center for Data Mining and Systems Biology College of Electrical Engineering Zhejiang University Hangzhou310027 China

This paper presents the design, modeling, and experimental validation of CapsuleBot, a novel hybrid aerial-ground bi-copter robot designed for long-endurance and low-noise operations. CapsuleBot combines the maneuverability of a bi-copter in the air with the low power consumption and low noise of a two-wheel self-balancing robot on the ground. To achieve this, we design an innovative mechanical structure named the actuated-wheel-rotor, which uses a servo motor and a brushless motor to function as both a tilting rotor in the air and an actuated wheel on the ground. CapsuleBot is equipped with two actuated-wheel-rotors, enabling it to achieve hybrid aerial-ground propulsion using only four motors, with no additional motors required compared to a bi-copter. Additionally, we develop comprehensive dynamics and control systems for both air and wheel mode, based on the bi-copter model and the two-wheel self-balancing robot model. A prototype of CapsuleBot is constructed, and its performance in terms of low power consumption and low noise is validated through experiments. Challenging tasks demonstrate CapsuleBot’s capability to climb steep, fly over cliffs, and traverse rough terrains. Copyright © 2023, The Authors. All rights reserved.

关键词： Antenna grounds

Joint Design of Radar Receive Filter and Unimodular ISAC Waveform with Sidelobe Level Control

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arXiv 2025年

作者： Zhang, Kecheng Liu, Ya-Feng Wang, Zhongbin Yuan, Weijie Keskin, Musa Furkan Wymeersch, Henk Xia, Shuqiang School of System Design and Intelligent Manufacturing The Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology Shenzhen518055 China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Department of Electrical Engineering Chalmers University of Technology Gothenburg41296 Sweden ZTE Corporation The State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen518055 China

Integrated sensing and communication (ISAC) has been considered a key feature of next-generation wireless networks. This paper investigates the joint design of the radar receive filter and dual-functional transmit waveform for the multiple-input multiple-output (MIMO) ISAC system. While optimizing the mean square error (MSE) of the radar receive spatial response and maximizing the achievable rate at the communication receiver, besides the constraints of full-power radar receiving filter and unimodular transmit sequence, we control the maximum range sidelobe level, which is often overlooked in existing ISAC waveform design literature, for better radar imaging performance. To solve the formulated optimization problem with convex and nonconvex constraints, we propose an inexact augmented Lagrangian method (ALM) algorithm. For each subproblem in the proposed inexact ALM algorithm, we custom-design a block successive upper-bound minimization (BSUM) scheme with closed-form solutions for all blocks of variable to enhance the computational efficiency. Convergence analysis shows that the proposed algorithm is guaranteed to provide a stationary and feasible solution. Extensive simulations are performed to investigate the impact of different system parameters on communication and radar imaging performance. Comparison with the existing works shows the superiority of the proposed algorithm. © 2025, CC BY-NC-SA.

关键词： Mean square error

CylinderTag: An Accurate and Flexible Marker for Cylinder-Shape Objects Pose Estimation Based on Projective Invariants

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arXiv 2023年

作者： Wang, Shaoan Zhu, Mingzhu Hu, Yaoqing Li, Dongyue Yuan, Fusong Yu, Junzhi State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing100871 China Department of Mechanical Engineering Fuzhou University Fuzhou350000 China National Engineering Laboratory for Digital and Material Technology of Stomatology Center of Digital Dentistry Peking University School Hospital of Stomatology Beijing100190 China

High-precision pose estimation based on visual markers has been a thriving research topic in the field of computer vision. However, the suitability of traditional flat markers on curved objects is limited due to the diverse shapes of curved surfaces, which hinders the development of high-precision pose estimation for curved objects. Therefore, this paper proposes a novel visual marker called CylinderTag, which is designed for developable curved surfaces such as cylindrical surfaces. CylinderTag is a cyclic marker that can be firmly attached to objects with a cylindrical shape. Leveraging the manifold assumption, the cross-ratio in projective invariance is utilized for encoding in the direction of zero curvature on the surface. Additionally, to facilitate the usage of CylinderTag, we propose a heuristic search-based marker generator and a high-performance recognizer as well. Moreover, an all-encompassing evaluation of CylinderTag properties is conducted by means of extensive experimentation, covering detection rate, detection speed, dictionary size, localization jitter, and pose estimation accuracy. CylinderTag showcases superior detection performance from varying view angles in comparison to traditional visual markers, accompanied by higher localization accuracy. Furthermore, CylinderTag boasts real-time detection capability and an extensive marker dictionary, offering enhanced versatility and practicality in a wide range of applications. Experimental results demonstrate that the CylinderTag is a highly promising visual marker for use on cylindrical-like surfaces, thus offering important guidance for future research on high-precision visual localization of cylinder-shaped objects. The code is available at: https://***/wsakobe/CylinderTag. Copyright © 2023, The Authors. All rights reserved.

关键词： Cylinders (shapes)

Enhanced Diagnosis of Lithium-Ion Battery Health in Electric Vehicles Through Advanced Hybrid Deep Learning Model Incorporating Attention Mechanism

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Enhanced Diagnosis of Lithium-Ion Battery Health in Electric...

Artificial Intelligence & Green Energy (ICAIGE), IEEE International Conference on

作者： Walid Mchara Mohamed Abdellatif Khalfa Lazhar Manai Laboratory of Robotics Informatics and Complex Systems (RISC) National Engineering School of Tunis (ENIT) University of El Manar Le Belvedere Tunis Higher Institute of Information and Communication Technologies Hamam Chatt Tunisia CRETn LaNSER Laboratory Borj-Cedria RISC Le Belvédère Tunis Tunisia ENIT University of El Manar

ISBN: (数字)9798350389838

ISBN: (纸本)9798350389845

With the rising adoption of lithium-ion batteries(LIBs) in electric vehicles, significant research efforts have been dedicated to ensuring the safe and reliable performance of Battery Management systems (BMS). Accurately estimating the State of Health (SOH), a crucial aspect of BMS functionality, is imperative for the secure operation of electric vehicles. To tackle this challenge, we propose a time series model designed specifically for forecasting the State of Health (SOH) of Li-ion batteries. Our approach integrates a CNN with a Long Short-Term Memory (LSTM) architecture, augmented by an attention mechanism. Experimental findings demonstrate that this LSTM-based approach significantly enhances prediction accuracy. The outcomes of this investigation present a promising avenue for improving the dependability and efficiency of electric vehicle battery systems, ultimately advancing the widespread adoption and sustainability of electric transportation.

关键词： Lithium-ion batteries Deep learning Attention mechanisms Time series analysis Transportation Predictive models Prediction algorithms Trajectory Convolutional neural networks Long short term memory

Feedback Shaping for Boolean Networks

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IFAC-PapersOnLine 2023年第2期56卷 6684-6689页

作者： Hongsheng Qi Maria Elena Valcher Guodong Shi Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing 100049 China Dipartimento di Ingegneria dell'Informazione Universita’ di Padova Padova 35131 Italy Australian Center for Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney NSW 2006 Australia

Boolean networks, as logical dynamical systems where the system states are Boolean variables, arise from applications in biology, computer networks, and social networks etc. In this paper, we present a framework to evaluate whether and how the closed-loop dynamics of a controlled Boolean network can be shaped into any prescribed form by state-feedback control. We refer to this problem as to the feedback shaping for Boolean networks. First of all, based on the linear representation of Boolean networks, we establish a necessary and sufficient rank condition for a controlled Boolean network to be feedback shapable or not. Next, we design an algorithm for the synthesis of closed-loop dynamics for a feedback shapable Boolean network, such that for any given controlled Boolean network and a desired closed-loop dynamics, one can always find a feedback control law so that the closed-loop dynamics is precisely realized.

关键词： Boolean networks feedback shaping

Roller-Quadrotor: A Novel Hybrid Terrestrial/Aerial Quadrotor with Unicycle-Driven and Rotor-Assisted Turning

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arXiv 2023年

作者： Zheng, Zhi Wang, Jin Wu, Yuze Cai, Qifeng Yu, Huan Zhang, Ruibin Tu, Jie Meng, Jun Lu, Guodong Gao, Fei The State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310027 China Robotics Institute of Zhejiang University Hangzhou310027 China Robotics Research Center of Yuyao City Ningbo315400 China The State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China Huzhou Institute of Zhejiang University Huzhou313000 China Center for Data Mining and Systems Biology College of Electrical Engineering Zhejiang University Hangzhou310027 China

The Roller-Quadrotor is a novel quadrotor that combines the maneuverability of aerial drones with the endurance of ground vehicles. This work focuses on the design, modeling, and experimental validation of the Roller-Quadrotor. Flight capabilities are achieved through a quadrotor configuration, with four thrust-providing actuators. Additionally, rolling motion is facilitated by a unicycle-driven and rotor-assisted turning structure. By utilizing terrestrial locomotion, the vehicle can overcome rolling and turning resistance, thereby conserving energy compared to its flight mode. This innovative approach not only tackles the inherent challenges of traditional rotorcraft but also enables the vehicle to navigate through narrow gaps and overcome obstacles by taking advantage of its aerial mobility. We develop comprehensive models and controllers for the Roller-Quadrotor and validate their performance through experiments. The results demonstrate its seamless transition between aerial and terrestrial locomotion, as well as its ability to safely navigate through gaps half the size of its diameter. Moreover, the terrestrial range of the vehicle is approximately 2.8 times greater, while the operating time is about 41.2 times longer compared to its aerial capabilities. These findings underscore the feasibility and effectiveness of the proposed structure and control mechanisms for efficient navigation through challenging terrains while conserving energy. Copyright © 2023, The Authors. All rights reserved.

关键词： Antennas

Graph-Based Visual-Kinematic Fusion and Monte Carlo Initialization for Fast-Deployable Cable-Driven Robots

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Graph-Based Visual-Kinematic Fusion and Monte Carlo Initiali...

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

作者： R. Khorrambakht H. Damirchi M.R. Dindarloo A. Saki S.A. Khalilpour Hamid D. Taghirad Stephan Weiss Electrical & Computer Engineering Department Control/Robotics Research Laboratory Tandon School of Engineering New York University Brooklyn NY School of Computer Science University of Adelaide Australia Faculty of Electrical Engineering University of Technology Tehran Iran Department of Smart Systems Technologies University of Klagenfurt Austria

Ease of calibration and high-accuracy task-space state-estimation purely based on onboard sensors is a key requirement for enabling easily deployable cable robots in real-world applications. In this work, we incorporate the onboard camera and kinematic sensors to drive a statistical fusion framework that presents a unified localization and calibration system which requires no initial values for the kinematic parameters. This is achieved by formulating a Monte-Carlo algorithm that initializes a factor-graph representation of the calibration and localization problem. With this, we are able to jointly identify both the kinematic parameters and the visual odometry scale alongside their corresponding uncertainties. We demonstrate the practical applicability of the framework using our state-estimation dataset recorded with the ARAS-CAM suspended cable driven parallel robot, and published as part of this manuscript.

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How2comm: communication-efficient and collaboration-pragmatic multi-agent perception 23

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How2comm: communication-efficient and collaboration-pragmati...

Proceedings of the 37th International Conference on Neural Information Processing systems

作者： Dingkang Yang Kun Yang Yuzheng Wang Jing Liu Zhi Xu Rongbin Yin Peng Zhai Lihua Zhang Academy for Engineering and Technology Fudan University and Cognition and Intelligent Technology Laboratory (CIT Lab) Academy for Engineering and Technology Fudan University FAW (Nanjing) Technology Development Company Ltd Academy for Engineering and Technology Fudan University and Cognition and Intelligent Technology Laboratory (CIT Lab) and Engineering Research Center of AI and Robotics Ministry of Education and AI and Unmanned Systems Engineering Research Center of Jilin Province

Multi-agent collaborative perception has recently received widespread attention as an emerging application in driving scenarios. Despite the advancements in previous efforts, challenges remain due to various dilemmas in the perception procedure, including communication redundancy, transmission delay, and collaboration heterogeneity. To tackle these issues, we propose How2comm, a collaborative perception framework that seeks a trade-off between perception performance and communication bandwidth. Our novelties lie in three aspects. First, we devise a mutual information-aware communication mechanism to maximally sustain the informative features shared by collaborators. The spatial-channel filtering is adopted to perform effective feature sparsification for efficient communication. Second, we present a flow-guided delay compensation strategy to predict future characteristics from collaborators and eliminate feature misalignment due to temporal asynchrony. Ultimately, a pragmatic collaboration transformer is introduced to integrate holistic spatial semantics and temporal context clues among agents. Our framework is thoroughly evaluated on several LiDAR-based collaborative detection datasets in real-world and simulated scenarios. Comprehensive experiments demonstrate the superiority of How2comm and the effectiveness of all its vital components. The code will be released at https://***/ydk122024/How2comm.

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