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International Conference on Intelligent Transportation

作者： Luyao Zhang Shaohang Han Sergio Grammatico Delft Center for Systems and Control TU Delft The Netherlands Department of Cognitive Robotics TU Delft The Netherlands

In this paper, we propose a novel behavior planner that combines game theory with search-based planning for automated lane merging. Specifically, inspired by human drivers, we model the interaction between vehicles as a gap selection process. To overcome the challenge of multi-modal behavior exhibited by the surrounding vehicles, we formulate the trajectory selection as a matrix game and compute an equilibrium. Next, we validate our proposed planner in the high-fidelity simulator CARLA and demonstrate its effectiveness in handling interactions in dense traffic scenarios.

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A Novel Unmanned Aerial System for Power Line Inspection and Maintenance Operations

A Novel Unmanned Aerial System for Power Line Inspection and...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： J.M. Marredo A. Petrus M.A. Trujillo A. Viguria A. Ollero CATEC (Advanced Center for Aerospace Technologies) Seville Spain Robotics Vision and Control Group (GRVC) Universidad de Sevilla Seville Spain

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

Ensuring the integrity and reliability of power lines is essential to maintain continuous service and avoid potential catastrophes. However, the increasingly extensive infrastructure represents formidable challenges in terms of inspection, maintenance, and worker safety. This paper presents the design, development and experimental validation of the Main Local Manipulation Platform (MLMP), a versatile aerial manipulator designed to install and remove a wide variety of devices on power lines while perched, without interrupting the power. The paper outlines the main design considerations, challenges encountered and solutions applied, including electrical protection, device manipulation and perching strategies. Multiple validation experiments, both in controlled and real scenarios, demonstrated the platform's effectiveness in the installation of clip-type bird diverters, cable separators and charging stations. The results underscore the potential of the MLMP to transform power line inspection and maintenance operations, improving the efficiency, reducing costs and ensuring worker safety.

关键词： Performance evaluation Particle separators Transforms Inspection Charging stations Birds Maintenance

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Event- Triggered based control of Robotic Arm under Denial of Service 21

Event- Triggered based Control of Robotic Arm under Denial o...

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21st International Multi-Conference on Systems, Signals and Devices, SSD 2024

作者： Abubakar, Abdulrazaq Nafiu Yahaya, Jamilu Umar Ma'Aruf, Muhammad Mysorewala, Muhammad Faizan Saif, Abdul-Wahid A. King Fahd University of Petroleum and Minerals Control and Instrumentation Engineering Department Dhahran31261 Saudi Arabia Interdisciplinary Research Center for Smart Mobility and Logistics King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia Interdisciplinary Research Center for Intelligent Manufacturing and Robotics King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia

ISBN: (纸本)9798350374131

In this paper, we studied the finite-time stability of robotic arm systems against Denial of Service attacks, when the link between the plant and the controller is often interrupted. In order to do this, a method is suggested that relies on an event-triggered mechanism which is based on the rate of change of the Lyapunov function, that keeps the system finite-time stable while simultaneously reducing the quantity of data interchange in the network. The suggested event-triggered finite-time controller's vulnerability to Denial of Service attacks is then assessed, and sufficient limitations on the length of a Denial of Service are identified to ensure the system's stability within a specified time frame. Lastly, a simulation study is used to show how effective the suggested strategy is. © 2024 IEEE.

关键词： System stability

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An Efficient Risk-aware Branch MPC for Automated Driving that is Robust to Uncertain Vehicle Behaviors

arXiv

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arXiv 2024年

作者： Zhang, Luyao Pantazis, George Han, Shaohang Grammatico, Sergio The Delft Center for Systems and Control Delft University of Technology Netherlands The Division of Robotics Perception and Learning KTH Royal Institute of Technology Sweden

One of the critical challenges in automated driving is ensuring safety of automated vehicles despite the unknown behavior of the other vehicles. Although motion prediction modules are able to generate a probability distribution associated with various behavior modes, their probabilistic estimates are often inaccurate, thus leading to a possibly unsafe trajectory. To overcome this challenge, we propose a risk-aware motion planning framework that appropriately accounts for the ambiguity in the estimated probability distribution. We formulate the risk-aware motion planning problem as a min-max optimization problem and develop an efficient iterative method by incorporating a regularization term in the probability update step. Via extensive numerical studies, we validate the convergence of our method and demonstrate its advantages compared to the state-of-the-art approaches. Copyright © 2024, The Authors. All rights reserved.

关键词： Iterative methods

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The Extended Optimal control Problem and Numerical Techniques of Its Solving

The Extended Optimal Control Problem and Numerical Technique...

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： Askhat Diveev Artem Barabash Department of Robotics Control Federal Research Center “Computer Science and Control” Russian Academy of Sciences Moscow Russia Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences Moscow Russia

A new numerical method for solving the optimal control problem in class practically implemented solutions is presented. The method uses an approach of the synthesized control and takes account uncertainties of initial states. Like as synthesized control the method move a control object changing location of stable equilibrium point. As a result it chooses from all possible optimal synthesized controls such, that less sensitive to changes of initial states. As an example, the optimal control problem of quadcopter with complex phase constraints in the form of obstacle areas and narrow bottle neck is considered. To solve this problem firstly the synthesis control problem is solved for obtaining stable equilibrium point in the state space by symbolic regression. After that positions of stable equilibrium points are searched according to source functional from the optimal control problem. As an example, the optimal control problem of quadcopter with complex phase constraints in the form of obstacle areas and narrow bottle neck is considered. To solve this problem firstly the synthesis control problem is solved for obtaining stable equilibrium point in the state space by symbolic regression. After that positions of stable equilibrium points are searched according to source functional from the optimal control problem. Additionally at the search of equilibrium point positions the goal functional is calculated as a sum of fuctional values for all given points of initial states.

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Algorithm for Detecting Surface Defects in Hot-Rolled Sheet Metal for Technical Vision Systems

Algorithm for Detecting Surface Defects in Hot-Rolled Sheet ...

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Information, control, and Communication Technologies (ICCT), International Conference on

作者： Vyacheslav V. Konyashov Alexey S. Sergeev Alexey V. Fedorov Kseniya A. Konyashova Oleg A. Kolganov Faculty of Control Systems and Robotics ITMO University Saint Petersburg Russia Researcher Scientific and Technical Center “Etalon” Saint Petersburg Russia

ISBN: (数字)9798331517564

ISBN: (纸本)9798331517571

The work presents the results of developing an algorithm for detecting surface defects in hot-rolled metal sheets for technical vision systems implementing the method of optical (laser) triangulation. The detection algorithm is implemented for a technical vision system based on a vision camera and a linear laser source. The results of experimental modeling are provided to determine the parameters of the optical detection scheme that meets the technological requirements of metal production. The experimental validation results of the detection algorithm for determining the sizes and locations of volumetric and planar surface defects are shown

关键词： Machine vision Surface emitting lasers Metals Process control Production Optical imaging Laser modes Laser transitions Laser applications Metal products

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Simultaneous Synthesis and Verification of Neural control Barrier Functions Through Branch-and-Bound Verification-in-the-Loop Training

Simultaneous Synthesis and Verification of Neural Control Ba...

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European control Conference (ECC)

作者： Xinyu Wang Luzia Knoedler Frederik Baymler Mathiesen Javier Alonso-Mora Cognitive Robotics Department Delft University of Technology Delft Netherlands Delft Center for Systems and Control Delft University of Technology Delft Netherlands

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

control Barrier Functions (CBFs) that provide formal safety guarantees have been widely used for safety-critical systems. However, it is non-trivial to design a CBF. Utilizing neural networks as CBFs has shown great success, but it necessitates their certification as CBFs. In this work, we leverage bound propagation techniques and the Branch-and - Bound scheme to efficiently verify that a neural network satisfies the conditions to be a CBF over the continuous state space. To accelerate training, we further present a framework that embeds the verification scheme into the training loop to synthesize and verify a neural CBF simultaneously. In partic-ular, we employ the verification scheme to identify partitions of the state space that are not guaranteed to satisfy the CBF conditions and expand the training dataset by incorporating additional data from these partitions. The neural network is then optimized using the augmented dataset to meet the CBF conditions. We show that for a non-linear control-affine system, our framework can efficiently certify a neural network as a CBF and render a larger safe set than state-of-the-art neural CBF works. We further employ our learned neural CBF to derive a safe controller to illustrate the practical use of our framework.

关键词： Scalability Neural networks Memory management Europe Aerospace electronics control systems Safety

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An Efficient Risk-aware Branch MPC for Automated Driving that is Robust to Uncertain Vehicle Behaviors

An Efficient Risk-aware Branch MPC for Automated Driving tha...

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IEEE Conference on Decision and control

作者： Luyao Zhang Georgios Pantazis Shaohang Han Sergio Grammatico Delft Center for Systems and Control Delft University of Technology The Netherlands Division of Robotics Perception and Learning KTH Royal Institute of Technology Sweden

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

One of the critical challenges in automated driving is ensuring safety of automated vehicles despite the unknown behavior of the other vehicles. Although motion prediction modules are able to generate a probability distribution associated with various behavior modes, their probabilistic estimates are often inaccurate, thus leading to a possibly unsafe motion plan. To overcome this challenge, we propose an Efficient RiskAware Branch MPC (EraBMPC) that appropriately accounts for the ambiguity in the estimated probability distribution. We formulate the risk-aware motion planning problem as a min-max optimization problem and develop an efficient iterative method by incorporating a regularization term in the probability update step. Via extensive numerical studies, we validate the convergence of our method and demonstrate its advantages compared to the state-of-the-art approaches.

关键词： Uncertainty Probabilistic logic Probability distribution Real-time systems Planning Safety Iterative methods Optimization Predictive control Convergence

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Realistic Unmanned Aerial Vehicle Simulation: A Comprehensive Approach

Realistic Unmanned Aerial Vehicle Simulation: A Comprehensiv...

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Iberian robotics Conference (ROBOT)

作者： David Tejero-Ruiz Francisco J. Pérez-Gran Antidio Viguria Aníbal Ollero CATEC (Advanced Center for Aerospace Technologies) Sevilla Spain Robotics Vision and Control Group (GRVC) Universidad de Sevilla Seville Spain

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

This paper presents a comprehensive software architecture that facilitates the testing and deployment of autonomous missions in the context of Unmanned Aerial Vehicle (UAV) simulation. Our approach integrates and enhances several tools, including the Robot Operating System (ROS), to create a robust environment for evaluating autonomous UAV operations and gathering data. The core of our simulation framework leverages Unreal Engine and the AirSim plugin to model UAV dynamics and generate sensor data. Various modifications have been implemented to enhance sensor fidelity and enable realistic movement of diverse world objects, achieving a higher degree of realism. Designed for high configurability, the proposed architecture allows for flexible adaptation to a wide range of scenarios and requirements. Thus, this simulation environment supports rigorous testing and development of autonomous UAV systems, presenting a valuable platform for researchers and developers in the field of aerial robotics.

关键词： Operating systems Heuristic algorithms Atmospheric modeling Virtual environments Computer architecture Autonomous aerial vehicles Robot sensing systems Vehicle dynamics Engines Testing

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Personalized gait trajectory generation based on anthropometric features using Random Forest

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Journal of Ambient Intelligence and Humanized Computing 2023年第12期14卷 15597-15608页

作者： Ren, Shixin Wang, Weiqun Hou, Zeng-Guang Chen, Badong Liang, Xu Wang, Jiaxing Peng, Liang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China The CAS Center for Excellence in Brain Science and Intelligence Technology Beijing100190 China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an710049 China

Using lower limb rehabilitation robots (LLRRs) to help stroke patients recover their walking ability is attracting more and more attention presently. Previous studies have shown that gait rehabilitation training with natural gait pattern can improve the therapeutic outputs. However, how to generate the personalized gait trajectory has not been well researched. In this paper, a personalized gait generation method based anthropometric features is proposed. Firstly, gait trajectories are fitted and simplified into Fourier coefficient vectors, which are used to represent gait trajectories. Secondly, fourteen body features are used to generate the personalized gait trajectories and the feature set is further optimized based on the minimal redundancy maximal relevance criterion for easy application on the LLRR. Then, the relationship between the optimized feature set and gait trajectories is modeled by using the RF algorithm. Finally, the performance of the proposed method is demonstrated by several comparison experiments. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Trajectories

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