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Human-Robot Collaboration Attack Based on Perception Deception

Human-Robot Collaboration Attack Based on Perception Decepti...

引用

automation, robotics and Computer Engineering (ICARCE), international conference on

作者： Yajie Liu Jie Ren Xianglong Meng Chuanbin Sun Yanzhi Dong Xiaohu Yuan School of Physics and Electronic Information Yantai University Yantai China Qiyuan Lab Beijing China

ISBN: (数字)9798331529505

ISBN: (纸本)9798331529512

Human-robot collaboration (HRC) plays a crucial role in various fields, highly relying on the perception capabilities of robots. While some literature explores HRC, research on potential attacks against HRC systems remains lacking. This research gap could lead to system vulnerabilities being exploited, affecting productivity and worker safety, and hindering the further adoption and application of HRC technology. We propose a perception-based deception attack method for HRC, which misguides the robot's perception to attack its decision-making, thereby impacting the effectiveness of human-robot collaboration. Our experiments involved a widely-used HRC task and demonstrated that perception deception could reduce the human-robot collaboration completion rate by over 36.67% and increase decision latency by 87.58%. The experimental results indicate that these attack methods can significantly reduce the robot's perception success rate. Through this research, we lay the foundation for further studies on improving the efficiency and robustness of human-robot collaboration.

关键词： Productivity automation Decision making Human-robot interaction Robustness Safety Delays Robots

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Freyja: A Full Multirotor System for Agile & Precise Outdoor Flights

Freyja: A Full Multirotor System for Agile & Precise Outdoor...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Shankar, Ajay Elbaum, Sebastian Detweiler, Carrick Univ Nebraska Dept Comp Sci & Engn Lincoln NE 68583 USA Univ Virginia Dept Comp Sci Charlottesville VA 22903 USA

ISBN: (纸本)9781728190778

Several independent approaches exist for state estimation and control of multirotor unmanned aerial systems (UASs) that address specific and constrained operational conditions. This work presents a complete end-to-end pipeline that enables precise, aggressive and agile maneuvers for multirotor UASs under real and challenging outdoor environments. We leverage state-of-the-art optimal methods from the literature for trajectory planning and control, such that designing and executing dynamic paths is fast, robust and easy to customize for a particular application. The complete pipeline, built entirely using commercially available components, is made open-source and fully documented to facilitate adoption. We demonstrate its performance in a variety of operational settings, such as hovering at a spot under dynamic wind speeds of up to 5-6m/s (12-15mi/h) while staying within 12 cm of 3D error. We also characterize its capabilities in flying high-speed trajectories outdoors, and enabling fast aerial docking with a moving target with planning and interception occurring in under 8 s.

关键词： Three-dimensional displays automation Trajectory planning Wind speed conferences Pipelines Trajectory

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QLSTM-Based Microgrid Daily Operation with Renewable Uncertainty

QLSTM-Based Microgrid Daily Operation with Renewable Uncerta...

引用

international conference on Control, automation, robotics and Vision (ICARCV)

作者： Zeina Bahij Najmus Sahar Bing Yan Department of Electrical and Microelectronic Engineering Rochester Institute of Technology Rochester NY USA

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

Microgrid is a small-scale grid where generation is close to the demand allowing more penetration of renewables, like photovoltaic (PV). However, the intermittent nature of PV power generation poses a significant challenge in microgrid operation, especially on days with highly variable weather conditions. In this paper, a deep reinforcement Q-learning long short-term memory (QLSTM) model is developed to predict the operation strategy of a microgrid for the next day at a 15-minute time interval. To address the uncertainty of PV power and demand, the previous three days' PV and load data are added as inputs to the model since weather conditions on consecutive days may depend on similar atmospheric conditions. Also, to address the effect of propagation of error in the long forecasting horizon with multiple steps, a moving window training method is implemented. The moving window will be shifted by 15 minutes at each step once the actual PV and load data are available till the end of the day. The model is tested in a microgrid consisting of combined cooling, heating and power, heat pump, PV, battery, and heating and cooling energy storage systems. Results show that our model outperforms gated recurrent unit, LSTM, and Q-learning for testing data from different months. Also, it shows better performance than MATLAB 2023 Optimization Toolbox (the branch-and-bound method) which uses forecasted data, especially on a day with highly variable weather conditions.

关键词： Costs Weather forecasting Microgrids Predictive models Mathematical models Data models Trigeneration Long short term memory Load modeling Testing

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Versatility of Low-Resolution Tactile Sensing for Edge and Pose Detection

Versatility of Low-Resolution Tactile Sensing for Edge and P...

引用

Artificial Intelligence, robotics and Control (AIRC), international conference on

作者： Dexter R. Shepherd Phil Husbands Andy Philippides Chris Johnson Dept. Informatics University of Sussex Brighton Sussex

ISBN: (数字)9798350385076

ISBN: (纸本)9798350385083

The paper explores the potential of low-resolution tactile sensors for edge and pose detection in robotics. We emphasise the efficiency and affordability of these sensors compared to high-resolution optical sensors, highlighting their practicality for diverse robotic applications. The study introduces a novel sensor design utilising a printed circuit board, which simplifies processing, enhances durability, and proves practical for various robotic platforms. The tactile sensors play a crucial role in optimising the robot's balance and providing an understanding of the robot's interaction with the environment. The fabrication of the low-resolution tactile sensor is detailed, and the methods used to gather tactile datasets for edge and orientation detection are explained, along with the techniques for training classifiers used with the sensor. Results of edge and orientation detection experiments are presented, and the challenges faced in generalising classification models to cover multiple textures and unseen data are analysed and discussed.

关键词： Legged locomotion Training Image edge detection Printed circuits Tactile sensors Predictive models Data models

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Automated Seed Quality Testing System Using GAN and Active Learning 1

引用

9th international conference on Pattern Recognition and Machine Intelligence (PReMI)

作者： Nagar, Sandeep Pani, Prateek Nair, Raj Varma, Girish Int Inst Informat Technol Hyderabad Machine Learning Lab Hyderabad India AdTech Corp Hyderabad India

ISBN: (数字)9783031127007

ISBN: (纸本)9783031126994;9783031127007

Quality assessment of agricultural produce is a crucial step in minimizing food stock wastage. However, this is currently done manually and often requires expert supervision, especially in smaller seeds like corn. We propose a novel computer vision-based system for automating this process. We build a novel seed image acquisition setup, which captures both the top and bottom views. Dataset collection for this problem has challenges of data annotation costs/time and class imbalance. We address these challenges by i.) using a Conditional Generative Adversarial Network (CGAN) to generate real-looking images for the classes with lesser images and ii.) annotate a large dataset with minimal expert human intervention by using a Batch Active Learning (BAL) based annotation tool. We benchmark different image classification models on the dataset obtained. We are able to get accuracies of up to 91.6% for testing the physical purity of seed samples.

关键词： Agriculture Quality Testing Generative methods Active Learning automation Computer Vision Image Classification

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The Multi-target Tracking Algorithm Based on the MM-GLMB Filter with Doppler Information 4

The Multi-target Tracking Algorithm Based on the MM-GLMB Fil...

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4th international conference on robotics, Control and automation Engineering (RCAE) / 4th international conference on Advanced Mechanical and Electrical Engineering (AMEE)

作者： Wang, Huibo Zhao, Tongzhou Wu, Weihua Lu, Menglin Xiong, Li Wuhan Inst Technol Sch Comp Sci & Engn Wuhan Peoples R China Air Force CPLA Air Force Early Warning Acad Wuhan Peoples R China

ISBN: (纸本)9781665427302

The traditional multi-target tracking (MTT) algorithm only uses the position information of the target for target tracking, which is prone to more false alarms when dealing with the multi-target tracking problem in the dense clutter environment, and it will increase the complexity and computation of data processing, and even generate the false tracks or lose tracks. In addition, the threshold of tracking gate of the traditional MTT algorithm is fixed, and the probability of target miss detection or false alarm is greatly increased in dense clutter environment. Aiming at the above problems, a tracker is built in order to improve the tracking performance in this paper. Firstly, Doppler information (or radial velocity) is introduced based on the multiple models generalized labeled multi-Bernoulli (MM-GLMB) filter under the consideration of the correlation between range and radial velocity. Secondly, the multi-dimension tracking gate is constructed with the information of target position and velocity in polar coordinate system, and the threshold of the multi-dimension tracking gate is adjusted through a maximum likelihood adaptive method. Finally, the state of target is updated using position measurements followed by sequential updates using Doppler measurements for make full use of the Doppler information. The results of the experimental simulation show that introducing the Doppler information of the target based on MM-GLMB in the dense clutter environment and the processing of the measurements using the adaptive tracking gate can effectively suppress the clutter and significantly improve the tracking performance.

关键词： multi-target tracking multiple models generalized labeled multi-Bernoulli Doppler information adaptive tracking gate

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PoseFusion: Multi-Scale Keypoint Correspondence for Monocular Camera-to-Robot Pose Estimation in Robotic Manipulation

PoseFusion: Multi-Scale Keypoint Correspondence for Monocula...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Xujun Han Shaochen Wang Xiucai Huang Zhen Kan Department of Automation University of Science and Technology of China Hefei China School of Automation Chongqing University Chongqing China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Visual-based robot pose estimation is a fundamental challenge, involving the determination of the camera’s pose with respect to a robot. Conventional methods for camera-to-robot pose calibration rely on fiducial markers to establish keypoint correspondences. However, these approaches exhibit significant variability in accuracy and robustness, particularly in 2D keypoint detection. In this work, we present an end-to-end pose estimation approach that achieves camera-to-robot calibration using monocular images and keypoint information. Our method employs a two-level nested U-shaped architecture, featuring a bottom-level residual U-block to extract richer contextual information from diverse receptive fields to enhance keypoint refinement. By incorporating the perspective-n-point (PnP) algorithm and leveraging 3D robot joint keypoints, we establish correspondence of 3D coordinate points between the robot’s coordinate system and the camera’s coordinate system, facilitating accurate pose estimation. Experimental evaluations encompass real-world and synthetic datasets, demonstrating competitive results across three distinct robot manipulators.

关键词： Three-dimensional displays Accuracy Robot kinematics Pose estimation Manipulators Feature extraction Fiducial markers

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Stable and Safe Navigation Scheme for Mobile Robots Under Moving Obstacle Presence

Stable and Safe Navigation Scheme for Mobile Robots Under Mo...

引用

robotics, automation and Artificial Intelligence (RAAI), IEEE international conference on

作者： Michael A. Gunarso Tua A. Tamba Dept. of Electrical Engineering Center for Control Automation and Systems Engineering Faculty of Engineering Technology Parahyangan Catholic University Bandung Indonesia

ISBN: (数字)9798331520038

ISBN: (纸本)9798331520045

This paper reports a controller design methodology for a differential drive wheeled mobile robot (DDWMR) model which considers both safety and stability properties of the robot's operation. The proposed methodology first constructs a stabilizing controller using Control Lyapunov Function (CLF) concept and then generates a polynomial function-type reference trajectory to seamlessly connect the initial and final poses of the DDWMR. Subsequently, a Control Barrier Function (CBF) based scheme is used to ensure the safety of the DDWMR movement in avoiding moving obstacles while driving on the constructed reference trajectory. By the proposed CLF-CBF integration, the proposed approach offers an efficient solution for autonomous navigation of DDWMR in the presence of moving obstacles while also addresses the challenges posed by its nonholonomic constraint. The effectiveness of the proposed approach is shown through simulations which demonstrate the robot's ability to perform safe and stable collision-free movement and navigation.

关键词： Navigation Robot sensing systems Stability analysis Polynomials Trajectory Safety Mobile robots Collision avoidance Lyapunov methods Autonomous robots

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Optimal Sequential Stochastic Deployment of Multiple Passenger Robots

Optimal Sequential Stochastic Deployment of Multiple Passeng...

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IEEE international conference on robotics and automation (ICRA)

作者： Lee, Chris (Yu Hsuan) Best, Graeme Hollinger, Geoffrey A. Oregon State Univ Collaborat Robot & Intelligent Syst CoRIS Inst Corvallis OR 97331 USA

ISBN: (纸本)9781728190778

We present a new algorithm for deploying passenger robots in marsupial robot systems. A marsupial robot system consists of a carrier robot (e.g., a ground vehicle), which is highly capable and has a long mission duration, and at least one passenger robot (e.g., a short-duration aerial vehicle) transported by the carrier. We optimize the performance of passenger robot deployment by proposing an algorithm that reasons over uncertainty by exploiting information about the prior probability distribution of features of interest in the environment. Our algorithm is formulated as a solution to a sequential stochastic assignment problem (SSAP). The key feature of the algorithm is a recurrence relationship that defines a set of observation thresholds that are used to decide when to deploy passenger robots. Our algorithm computes the optimal policy in O(NR) time, where N is the number of deployment decision points and R is the number of passenger robots to be deployed. We conducted drone deployment exploration experiments on real-world data from the DARPA Subterranean challenge to test the SSAP algorithm. Our results show that our deployment algorithm outperforms other competing algorithms, such as the classic secretary approach and baseline partitioning methods, and is comparable to an offline oracle algorithm.

关键词： Uncertainty automation conferences Probability distribution Land vehicles Partitioning algorithms Robots

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Vector models for Modeling Logic Based on XOR-Relations 16

Vector Models for Modeling Logic Based on XOR-Relations

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16th IEEE international conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering, TCSET 2022

作者： Hahanov, Vladimir Litvinova, Eugenia Shevchenko, Olga Chumachenko, Svetlana Khakhanova, Hanna Hahanov, Ivan Kharkov National University of Radioelectronics Design Automation Department Kharkov Ukraine

ISBN: (纸本)9781665468619

A model of relations between logical functions is proposed, which are used for the synthesis of digital circuits. Relation structures use the XOR-operation, which allows solving problems of technical diagnostics, such as creating fault models, fault modeling, test synthesis, evaluation of their quality, and diagnosis of single and multiple constant defects. A method for the synthesis of deductive formulas based on the use of binary vectors to describe the behavior of logical elements is proposed. methods for deductive analysis of digital elements based on the use of tabular, analytical and vector models are proposed. Examples of constructing deductive formulas for modeling faults on test sets are given. Estimates of the computational complexity of the methods are given in order to demonstrate the advantages of vector data structures and the corresponding method of deductive analysis. © 2022 IEEE.

关键词： Vectors

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