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Attitude Balance Control of a Wheeled Quadruped Robot Utilizing an Inertial Measurement Unit

Attitude Balance Control of a Wheeled Quadruped Robot Utiliz...

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robotics, Control and automation (ICRCA), international conference on

作者： Xiyuan Li Yunsong Li Jihong Zhang Changshuai Sun School of Electromechanical and Automotive Engineering Yantai University Yantai China School of Information Science and Technology Beijing University of Technology Beijing China

ISBN: (数字)9798331544577

ISBN: (纸本)9798331544584

the Wheeled Quadruped Robot (WQR), a novel hybrid mobile platform that combines the advantages of wheeled and legged locomotion, has attracted significant research interest due to its enhanced mobility and stability in complex terrains. However, achieving efficient attitude stabilization during dynamic operations remains a critical technical challenge. this study initiates with a thorough kinematic modeling of the WQR mechanism. Next, we present a novel attitude stabilization methodology employing closed-loop control architecture driven by real-time Inertial Measurement Unit (IMU) data streams. Our approach integrates kinematic constraints and real-time IMU data with Proportional-Integral (PI) regulators to establish an inverse kinematics-guided adaptive adjustment mechanism. this mechanism dynamically adjusts leg movements in response to deviations in attitude. To assess the effectiveness of our control strategy under diverse terrain conditions and motion patterns, extensive simulations were conducted, comparing it with fixed joint angle control and traditional inverse kinematics-based control methods. the simulation results indicate that the WQR's attitude stability is markedly improved across various terrains and motion states after implementing our proposed control strategy. this research contributes to robotic control theory by innovatively integrating sensor fusion and adaptive kinematics, thereby significantly impacting the development of robust mobile platforms for unstructured environments.

关键词： Legged locomotion Adaptation models Measurement units Attitude control Kinematics Inertial navigation Robot sensing systems Stability analysis Real-time systems Quadrupedal robots

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MCTS Based Dispatch of Autonomous Vehicles under Operational Constraints for Continuous Transportation

MCTS Based Dispatch of Autonomous Vehicles under Operational...

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IEEE international conference on automation Science and Engineering (CASE)

作者： Milan Tomy Konstantin M. Seiler Andrew J. Hill University of Sydney NSW Australia University of Technology Sydney NSW Australia

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Continuous transportation of material in the mining industry is achieved by the dispatch of autonomous haul-trucks with discrete haulage capacities. Recently, Monte Carlo Tree Search (MCTS) was successfully deployed in tackling challenges of long-run optimality, scalability and adaptability in haul-truck dispatch. Typically, operational constraints imposed on the mine site are satisfied by heuristic controllers or human operators independent of the dispatch planning. this article incorporates operational constraint satisfaction into the dispatch planning by utilising the MCTS based dispatch planner Flow-Achieving Scheduling Tree (FAST). Operational constraint violation and satisfaction are modelled as opportunity costs in the combinatorial optimisation problem of dispatch. Explicit cost formulations are avoided by utilising MCTS generator models to derive opportunity costs. Experimental studies with four types of operational constraints demonstrate the success of utilising opportunity costs for constraint satisfaction, and the effectiveness of integrating constraints into dispatch planning.

关键词： Costs Monte Carlo methods Scalability Transportation Production Linear programming Generators Planning Mining industry Optimization

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Servo Drive with PWM Controller Simulation

Servo Drive with PWM Controller Simulation

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Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Vladislav D. Popov Yuriy V. Shornikov Dmitry N. Dostovalov Department of Automated Control Systems Novosibirsk State Technical University Novosibirsk Russia Department of Automated Control Systems Novosibirsk State Technical University Institute of Automation and Electrometry of the Siberian Branch of the Russian Academy of Sciences Novosibirsk Russia

ISBN: (数字)9798350389234

ISBN: (纸本)9798350353051

the simulating of a servo drive with symmetrical pulse width controlling is implemented by the ISMA platform. this task is classified as an event-continuous or hybrid system. Since the dynamic processes can be event-driven, the finite-state machine notation by D. Harel (statechart as formalism) is applied to build a mathematical model for the problem. the statechart with three states complying the Cauchy problem is designed, predicates for directed transitions, as well as states equations are defined. the original LISMA language, combining both block and textual coding, which allows to form compact models that correspond bijectively to statechart formalism used for event-driven continuous systems, is applied. A fragment of the LISMA language grammar for determining the states and transitions of hybrid systems is presented. the designed ISMA software is resolved by original explicit and semi-explicit numerical methods with the asymptotic algorithm for event detection, included to the ISMA library. Computer experiments demonstrate good results with sufficient accuracy.

关键词： Analytical models Computational modeling Software algorithms Pulse width modulation Mathematical models Software Libraries

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YOLOv8-GDI: A lightweight YOLOv8 for real-time Pedestrian Detection

YOLOv8-GDI: A lightweight YOLOv8 for real-time Pedestrian De...

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robotics, Control and automation Engineering (RCAE), international conference on

作者： Jianbin Sang Mengwen Zhang Huicheng Yang Ke Xu Yaocong Hu Haiting Wang Mengbo Jia Jun Yuan Anhui Polytechnic University Wuhu China

ISBN: (数字)9798350355642

ISBN: (纸本)9798350355659

Aiming at the current challenges of low detection efficiency in real-time pedestrian detection algorithms, complex model structures, and difficulties in implementing them on mobile devices, we proposed YOLOv8-GDI, a lightweight pedestrian detection model designed based on the backbone of YOLOv8n. Firstly, the C2f-Ghost module is constructed by incorporating the Ghost Convolution in the model, in order to decrease the number of floating-point operations during feature channel fusion and enhance feature expression capability. In addition, Dynamic Task Align Detection Head(DTADH) was designed to facilitate the interaction between the model classification and localization to further enhance the model's detection performance. Finally, the Inner-CIoU loss function was introduced into the YOLOv8n to improve the ability to localize features of different sizes. the experimental results show that compared with YOLOv8n, YOLOv8-GDI reduced the number of parameters by 50%, decreased the computational complexity by 25%, and maintained a high detection accuracy on the Wider person dataset. this suggested that the improved model is more lightweight and has better application value in the direction of real-time pedestrian detection.

关键词： Location awareness Adaptation models Pedestrians Accuracy Convolution Computational modeling Heuristic algorithms Feature extraction Real-time systems Computational complexity

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Methodology for Development Based on Ontological models Intelligent Services with Explanation Generation 7th

Methodology for Development Based on Ontological Models Inte...

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7th international Scientific conference on Intelligent Information Technologies for Industry, IITI 2023

作者： Gribova, Valeriya Shalfeeva, Elena Institute of Automation and Control Processes FEB RAS Vladivostok Russia Far Eastern Federal University Vladivostok Russia

ISBN: (纸本)9783031437885

In the early days of artificial intelligence, a knowledge base approach was used to solve non-formalizable problems and attempt to explain those solutions. As it has evolved, the range of applied methods has expanded, the number of available intelligent services has increased, and the complexity of tasks that can be solved has increased. However, there has been very little progress in the direction of explainability. Nowdays the situation has come close to using artificial intelligence systems for truly responsible decisions. Professionals who use "artificial" support need in explanation of chosen hypotheses no less than need in the hypotheses themselves. Ontological models and ontological methodology for the development of intelligent services provide the generation of an explanation for the proposed solutions in understandable terms. the article presents the architectural components of an intelligent service capable of explaining decisions. All components are built on the basis of a single domain ontology, including the ontology of knowledge and terminological dictionaries or reference books. As applied to problems solved in the domain, it is extended by ontologies of input data, ontologies for explaining hypotheses, and agreements on decision rules. the architectural components being created within the framework of such an ontology are typical, guaranteeing the property of explainability to an intelligent service. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Ontology

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Comparative Analysis of Uncertainty Quantification models in Active Learning for Efficient System Identification of Dynamical Systems

Comparative Analysis of Uncertainty Quantification Models in...

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IEEE international conference on automation Science and Engineering (CASE)

作者： Hans Mertens Frances Zhu Mechanical Engineering Robotics Space Exploration Lab University of Hawai‘i at Mānoa Hawai‘i Institute of Geophysics and Planetology University of Hawai‘i at Mānoa

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Active learning algorithms strategically select informative input samples, aiming to enhance understanding and optimize sample efficiency for dynamical systems. the efficacy of machine learning (ML) models with uncertainty quantification in identifying dynamical systems with different characteristics has not yet been explored. this paper investigates four ML models: Gaussian processes (GPs) with radial basis function (RBF), GPs with Matérn kernels, Bayesian neural networks (NNs) with Monte Carlo dropout(MCD), and ensemble neural networks (ENNs). Both continuous and non-continuous learning strategies are employed for all models. Five well known dynamical systems with different characteristics, state dimensionalities, and dynamical complexities are simulated to test the performance of the models along the metrics of test RMSE as well as samples and run time until convergence. through systematic experimentation, this paper provides guidance for researchers selecting models and algorithms in active learning for system identification, with insights into their strengths and limitations. Gaussian Processes with RBF kernels are shown to be the best overall choice while ENNs with Bayesian inference emerge as a scalable alternative, showing promise for high-dimensional tasks. Employing continuous training has proven to enhance the performance of Gaussian processes with RBF kernels, as well as ENNs, resulting in significant improvements in both sample and run-time efficiency.

关键词： Training Measurement Analytical models Uncertainty Monte Carlo methods Gaussian processes Artificial neural networks System identification Kernel Dynamical systems

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Zero-Shot Object Navigation with Vision-Language models Reasoning 27th

Zero-Shot Object Navigation with Vision-Language Models Reas...

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27th international conference on Pattern Recognition, ICPR 2024

作者： Wen, Congcong Huang, Yisiyuan Huang, Hao Huang, Yanjia Yuan, Shuaihang Hao, Yu Lin, Hui Liu, Yu-Shen Fang, Yi Lab New York University Abu Dhabi Abu Dhabi United Arab Emirates Center for Artificial Intelligence and Robotics New York University Abu Dhabi Abu Dhabi United Arab Emirates Tandon School of Engineering New York University New York United States University of Science and Technology of China Anhui China School of Software Tsinghua University Beijing China

ISBN: (纸本)9783031784552

Object navigation is crucial for robots, but traditional methods require substantial training data and cannot be generalized to unknown environments. Zero-shot object navigation (ZSON) aims to address this challenge, allowing robots to interact with unknown objects without specific training data. Language-driven zero-shot object navigation (L-ZSON) is an extension of ZSON that incorporates natural language instructions to guide robot navigation and interaction with objects. In this paper, we propose a novel Vision Language model with a Tree-of-thought Network (VLTNet) for L-ZSON. VLTNet comprises four main modules: vision language model understanding, semantic mapping, tree-of-thought reasoning and exploration, and goal identification. Among these modules, Tree-of-thought (ToT) reasoning and exploration module serves as a core component, innovatively using the ToT reasoning framework for navigation frontier selection during robot exploration. Compared to conventional frontier selection without reasoning, navigation using ToT reasoning involves multi-path reasoning processes and backtracking when necessary, enabling globally informed decision-making with higher accuracy. Experimental results on PASTURE and RobothOR benchmarks demonstrate the outstanding performance of our model in LZSON, particularly in scenarios involving complex natural language as target instructions. Videos are available at https://***/. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Semantics

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Integration of Slip Detection and Grip Force Control in an Autonomous Robot Assembly Task for Space Applications

Integration of Slip Detection and Grip Force Control in an A...

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IEEE international conference on automation Science and Engineering (CASE)

作者： I Ishrath S Barat Gustavo H. Diaz Shreya Santra Kazuya Yoshida Harish J. Palanthandalam-Madapusi Dept. of Mechanical Engineering IITGN Robotics Laboratory Indian Institute of Technology Gandhinagar India Depart. of Aerospace Engineering Graduate School of Engineering Space Robotics Laboratory (SRL) Tohoku University Sendai Japan

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Establishing human habitat using in-situ materials on the Moon or Mars autonomously by robotic systems is of great interest to humans. In such autonomous assembly tasks, it is crucial to integrate a slip detection capability that can detect any slipping in the grip and take corrective actions autonomously. this will enable safe handling of in-situ materials during assembly by not unnecessarily applying excessive gripping force. We construct and evaluate sliding slip detection methods (based on both heuristic and learning methods), using only the normal force recorded by a uni-axial force senor in a robotic gripper particularly from the point of view of autonomous assembly tasks for space applications. We were able to achieve over 75% sensitivity and specificity in slip detection using LSTM (Long Short-Term Memory) based model. We also observe that training the model on simulation data alone yields very robust performance in experiments and real-time prediction, and contrary to our expectation, labeling slip in the incipient phase did not yield better performance. Further, we integrate slip detection and corrective actions with an autonomous assembly task through Robot Operating System. In an experimental demonstration of autonomous assembly task using magnetic blocks, YOLO v8 for object detection and LSTM model for slip detection, our results indicate that we are able to successfully complete with correct detection of slip and corrective actions in 9 out of the 10 demonstrations.

关键词： Training YOLO Force Predictive models Aerospace electronics Real-time systems Data models Labeling Assembly Long short term memory

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Research on Path Tracking Control Method of Fully Driven AUV under Ocean Current Interference

Research on Path Tracking Control Method of Fully Driven AUV...

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IEEE international conference of Intelligent Robotic and Control Engineering (IRCE)

作者： Wanxi Zheng Automation Research Institute Lianyungang China

ISBN: (数字)9798350352399

ISBN: (纸本)9798350352405

Autonomous underwater vehicles (AUVs) play an important role in human understanding and management of the ocean. Fully actuated AUVs can achieve 6 degrees of freedom motion control, with high control accuracy and anti-interference ability, and have high application value in the field of underwater precision operations. this article vectorizes the modeling of a multi thruster fully driven underwater vehicle, establishes a path tracking error model in a non-projective Serret Frenet coordinate system, designs disturbance resistant kinematic and dynamic controllers using inverse control methods, and analyzes the stability of the designed controllers. the simulation results show that the controller can asymptotically stabilize path tracking error, velocity tracking error, and attitude tracking error.

关键词： Analytical models Uncertain systems Uncertainty Attitude control Oceans Simulation Interference Kinematics Vehicle dynamics Immune system

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Flexible Robot Dynamics and Vibration: From Analytical Modeling to Operational Modal Analysis

Flexible Robot Dynamics and Vibration: From Analytical Model...

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international conference on Autonomous Robots and Agents, ICARA

作者： Viet-Hung Vu Zhaoheng Liu Marc thomas Dept. of Mechanical and Aerospace Engineering Royal Military College of Canada Kingston ON Canada Dept. of Mechanical Engineering École de technologie supérieure Montreal QC Canada

ISBN: (数字)9798350394245

ISBN: (纸本)9798350394252

this paper presents recent studies on the dynamics and vibration of a flexible robot developed for industrial use that features six degrees of freedom. the flexibility of the joints and links is considered. We investigate the nonlinear dynamics and non-stationary vibration behavior of the robot's structure during grinding applications using both analytical and experimental methods. A linearization technique is introduced for the analytical modeling of the robot's dynamics across its entire workspace. Experimental investigations include modal testing and operational modal analysis, utilizing autoregressive models (ARX) and the Kalman filter to accurately characterize the robot's dynamic properties, dynamic contact forces, and the adaptation of these parameters in non-stationary vibrations. the effective performance of both approaches and the congruence between analytical and experimental findings suggest the potential for a hybrid modal analysis technique, tailored for flexible structures and robots operating under complex, real-world conditions.

关键词： Vibrations Analytical models Adaptation models Service robots Modal analysis Dynamics Mathematical models

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