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American Control Conference (ACC)

作者： Han Gao W. Pengying S. Yao Kangjie Zhou M. Ji Hangxin Liu Chang Liu Department of Advanced Manufacturing and Robotics College of Engineering Peking University National Key Laboratory of General Artificial Intelligence Beijing Institute for General Artificial Intelligence (BIGAI)

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

Target tracking has numerous significant civilian and military applications, and maintaining the visibility of the target plays a vital role in ensuring the success of the tracking task. Existing visibility-aware planners primarily focus on keeping the target within the limited field of view of an onboard sensor and avoiding obstacle occlusion. However, the negative impact of system uncertainty is often neglected, rendering the planners delicate to uncertainties in practice. To bridge the gap, this work proposes a model predictive control (MPC)-based trajectory planner for real-time visibility-aware and safe target tracking in the presence of system uncertainty. For more accurate target motion prediction, we introduce the concept of belief-space probability of detection (BPOD) to measure the predictive visibility of the target under stochastic robot and target states. An Extended Kalman Filter variant incorporating BPOD is developed to predict target belief state under uncertain visibility within the planning horizon. To reach real-time trajectory planning, we propose a computationally efficient algorithm to uniformly calculate both BPOD and the chance-constrained collision risk by utilizing linearized signed distance function (SDF), and subsequently solve the MPC problem by sequential convex programming. Extensive simulation results with benchmark comparisons show the capacity of the proposed approach to robustly maintain the visibility of the target under high system uncertainty. The practicality of the proposed trajectory planner is validated by real-world experiments.

关键词： Uncertainty Target tracking Trajectory planning Stochastic systems Simulation Stochastic processes Robot sensing systems

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Real-Time Plant Recognition and Crop Row Navigation for Autonomous Precision Agricultural Sprayer Robot

Real-Time Plant Recognition and Crop Row Navigation for Auto...

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International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Fazal Nasir Muhammad Haris Bilawal Khan Muhammad Tufail Muhammad Tahir Khan Zhang Dong Advanced Robotics and Automation Lab National Center of Robotics and Automation Peshawar Pakistan Department of Mechatronics Engineering University of Engineering and Technology Peshawar Pakistan Institute of Automation Qilu University of Technology (Shandong Academy of Sciences) Jinan China

This paper presents a vision-based selective spraying technique for an autonomous agricultural sprayer robot. In traditional methods, excessive chemical spraying cause deleterious effects on human health, environment and becomes uneconomical. In order to reduce the agrochemical wastage encounters in a broadcast spraying, a selective plant spraying method is used for crop chemical treatment. The sensor-based approach assisted with YOLOv7 model is deployed on a custom designed robot for recognizing and localizing the lettuce plants in field. The PID-based pressure controller is designed that minimizes the undesirable fluctuations cause by the opening/closing of solenoid-valve-nozzles (SVNs) during spraying. Thus the nozzle's spraying quality is maintained by keeping the pressure constant to a desired value. A visual servoing scheme for row tracking is presented that uses the detected plant's spatial features. The robustness of the visual-based navigation is validated in the real field experiments.

关键词： Service robots Plants (biology) Spraying Crops Wheels Robot sensing systems Visual servoing

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AI Fairness-From Machine Learning to Federated Learning

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Computer Modeling in engineering & Sciences 2024年第5期139卷 1203-1215页

作者： Lalit Mohan Patnaik Wenfeng Wang Consciousness Studies Program School of HumanitiesNational Institute of Advanced StudiesBangalore560012India Research Institute of Intelligent Engineering and Data Applications Shanghai Institute of TechnologyShanghai201418China Research Center of Ecology and Environment of Central Asia Chinese Academy of SciencesUrumqi830011China Applied Nonlinear Science Lab Anand International College of EngineeringJaipur391320India London Institute of Technology The ASE-London CTI of SCOLondonCR26EQUK Sino-Indian Joint Research Center of AI and Robotics The IMT InstituteBhubaneswar752054India

This article reviews the theory of fairness in AI-frommachine learning to federated learning,where the constraints on precision AI fairness and perspective solutions are also *** a reliable and quantitative evaluation of AI fairness,many associated concepts have been proposed,formulated and ***,the inexplicability of machine learning systems makes it almost impossible to include all necessary details in the modelling stage to ensure *** privacy worries induce the data unfairness and hence,the biases in the datasets for evaluating AI fairness are *** imbalance between algorithms’utility and humanization has further reinforced *** for federated learning systems,these constraints on precision AI fairness still *** solution is to reconcile the federated learning processes and reduce biases and imbalances accordingly.

关键词： Formulation evaluation classification constraints imbalance biases

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You Only Scan Once: A Dynamic Scene Reconstruction Pipeline for 6-DoF Robotic Grasping of Novel Objects

arXiv

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arXiv 2024年

作者： Zhou, Lei Wang, Haozhe Zhang, Zhengshen Liu, Zhiyang Tay, Francis E.H. Ang, Marcelo H. The Advanced Robotics Centre National University of Singapore 117608 Singapore The Integrative Sciences and Engineering Pro-gramme National University of Singapore Graduate School 119077 Singapore

In the realm of robotic grasping, achieving accurate and reliable interactions with the environment is a pivotal challenge. Traditional methods of grasp planning methods utilizing partial point clouds derived from depth image often suffer from reduced scene understanding due to occlusion, ultimately impeding their grasping accuracy. Furthermore, scene reconstruction methods have primarily relied upon static techniques, which are susceptible to environment change during manipulation process limits their efficacy in real-time grasping tasks. To address these limitations, this paper introduces a novel two-stage pipeline for dynamic scene reconstruction. In the first stage, our approach takes scene scanning as input to register each target object with mesh reconstruction and novel object pose tracking. In the second stage, pose tracking is still performed to provide object poses in real-time, enabling our approach to transform the reconstructed object point clouds back into the scene. Unlike conventional methodologies, which rely on static scene snapshots, our method continuously captures the evolving scene geometry, resulting in a comprehensive and up-to-date point cloud representation. By circumventing the constraints posed by occlusion, our method enhances the overall grasp planning process and empowers state-of-the-art 6-DoF robotic grasping algorithms to exhibit markedly improved accuracy. Copyright © 2024, The Authors. All rights reserved.

关键词： Pipelines

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Fractional Kelvin-Voigt based Viscoelastic Control for self-Balancing Exoskeleton

Fractional Kelvin-Voigt based Viscoelastic Control for self-...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Li, Wentao Li, Feng Yang, Ming Li, Jinke Li, Ming Zhu, Yuanpei Yin, Meng Tian, Dingkui Wu, Xinyu Southern University of Science and Technology Department of Electronic and Electrical Engineering Shenzhen518055 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518005 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518005 China University of Science and Technology of China Hefei230026 China

ISBN: (纸本)9798350325706

Self-balancing exoskeleton robots enable hands-free walking for the wearer, and the problem of its stable walking has been a challenge. In this paper, to achieve compliant and stable walking of a self-balancing exoskeleton robot and reduce the shock between the robot and the ground, we propose a new fractional kelvin voigt viscoelastic controller (FKVC). The proposed FKVC incorporates the advantages of fractional order and the kelvin voigt viscoelastic to endow the self-balancing exoskeleton with stable and dynamic walking capabilities. Simulation results show that the actual CoM position of the exoskeleton well tracks the reference CoM position, and the actual ZMP converges to the reference ZMP position. The ZMP is always within the effective support region of the biped. Therefore, we experimentally proved the practicality and effectiveness of the FKVC method, and the self-balancing exoskeleton successfully realizes stable dynamic walking. © 2023 IEEE.

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A Soft Pneumatic Actuator with Multiple Motion Patterns Based on Length-tuning Strain-limiting Layers

A Soft Pneumatic Actuator with Multiple Motion Patterns Base...

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IEEE International Conference on Soft robotics (RoboSoft)

作者： Quan Xiong Xuanyi Zhou Chen-Hua Yeow Department of Biomedical Engineering Advanced Robotics Centre National University of Singapore Singapore Singapore Department of Biomedical Engineering National University of Singapore Singapore Singapore

Soft pneumatic actuator with strain-limiting layers has played an important role in soft robotics in the last decades. However, limited by their pre-designed and permanent strain-limiting layers, their motion pattern is usually single. Here, we proposed a soft pneumatic actuator with multiple motion patterns based on length-tuning strain-limiting layers. We integrated 4 cable-based strain-limiting layers into a 3D printed soft pneumatic actuator. A cable locking system is proposed to lock the cables as strain-limiting layers. The system is actuated by a small fabric balloon and can provide up to 79 N blocking force. With a rotatory sensor, it can also monitor the actual length of the cable. The soft pneumatic actuator can achieve omnidirectional bending and extension by regulating the state of the 4 cable locking systems. By experiments, we verify the work principle of cable locking system. The actuator here can also vary its stiffness from 6 N/m to 97 N/m by antagonism.

关键词： Pneumatic actuators Three-dimensional displays Friction Force Soft robotics Bending Programming

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SDFT: Structural Discrete Fourier Transform for Place Recognition and Traversability Analysis

SDFT: Structural Discrete Fourier Transform for Place Recogn...

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

作者： Ayumi Umemura Ken Sakurada Masaki Onishi Kazuya Yoshida Department of Aerospace Engineering Space Robotics Lab. (SRL) Graduate School of Engineering Tohoku University Sendai Japan The National Institute of Advanced Industrial Science and Technology (AIST) Tokyo Japan

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

The ability to associate the current location with previously visited places is an essential aspect of autonomous ground robots. Unstructured environments such as planetary surfaces pose a significant challenge for robots because their terrain is less distinctive. Meanwhile, traversability must be analyzed simultaneously for safe navigation. In the past, place recognition research has rarely considered traversability analysis despite its significance. This is because the structural information of terrains becomes quickly implicit during the encoding process. This paper provides a method that explicitly addresses both problems: place recognition and traversability analysis. It proposes a discrete Fourier transform (DFT) to represent the frequency components embedded in ground curvature, which underlies both concepts. Our place recognition function demonstrates excellent performance in extensive experiments using challenging planetary & urban datasets while estimating traversability that other approaches find difficult to handle.

关键词： Point cloud compression Accuracy Simultaneous localization and mapping Navigation Discrete Fourier transforms Urban areas Noise Robustness Path planning Surface treatment

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Exploring Robust and Explainable Design for Facial Expression-Based Emotional State Estimation in Children with Profound Intellectual Multiple Disabilities

Exploring Robust and Explainable Design for Facial Expressio...

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European Signal Processing Conference (EUSIPCO)

作者： Kota Mochida Teppei Nakano Shinya Fujie Mari Wakabayashi Tomomi Sato Tetsuji Ogawa Department of Communications and Computer Engineering Waseda University Department of Advanced Robotics Chiba Institute of Technology Department of Nursing Graduate School of Medicine Yokohama City University

ISBN: (数字)9789464593617

ISBN: (纸本)9798331519773

We explored the use of pre-trained models to estimate the emotional states of children with profound intellectual multiple disabilities (PIMD) from face images. The ability of these children to express emotional states and the methods through which they do so vary from child to child, fulfilling two crucial requirements is essential for employing pattern recognition-based emotional state estimation in nursing care decision-making: i) constructing a system with limited data and ii) ensuring the explanation of prediction rationale. We aim to meet these requirements by employing a large-scale pre-trained model, specifically designed to detect action units (AUs) representing facial muscle movements, serving as a feature extractor for extracting emotional state representations. Detecting AUs to measure facial muscle movements is directly associated with facial expressions and can be done using the same model for both healthy individuals and children with PIMD. This allows the construction of a feature extractor without the need for extensive data from children with PIMD. Moreover, we anticipate that AUs can serve as explanatory material for explaining the rationale behind emotional state estimations. To validate the proposed approach's effectiveness, we conducted comfort state estimation using video data of a child capable of expressing emotional states through facial expressions. Our results demonstrated the effectiveness of the proposed approach compared to an approach using a general pre-trained model.

关键词： Pediatrics Face recognition Medical services Machine learning Signal processing Predictive models Feature extraction Facial muscles Motion measurement State estimation

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ASPIRe: An Informative Trajectory Planner with Mutual Information Approximation for Target Search and Tracking

ASPIRe: An Informative Trajectory Planner with Mutual Inform...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Kangjie Zhou Pengying Wu Yao Su Han Gao Ji Ma Hangxin Liu Chang Liu Department of Advanced Manufacturing and Robotics College of Engineering Peking University National Key Laboratory of General Artificial Intelligence Beijing Institute for General Artificial Intelligence (BIGAI)

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper proposes an informative trajectory planning approach, namely, adaptive particle filter tree with sigma point-based mutual information reward approximation (ASPIRe), for mobile target search and tracking (SAT) in cluttered environments with limited sensing field of view. We develop a novel sigma point-based approximation to accurately estimate mutual information (MI) for general, non-Gaussian distributions utilizing particle representation of the belief state, while simultaneously maintaining high computational efficiency. Building upon the MI approximation, we develop the Adaptive Particle Filter Tree (APFT) approach with MI as the reward, which features belief state tree nodes for informative trajectory planning in continuous state and measurement spaces. An adaptive criterion is proposed in APFT to adjust the planning horizon based on the expected information gain. Simulations and physical experiments demonstrate that ASPIRe achieves real-time computation and outperforms benchmark methods in terms of both search efficiency and estimation accuracy.

关键词： Accuracy Target tracking Trajectory planning Robot sensing systems Real-time systems Particle filters Trajectory

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An Incremental Planning Strategy-Based Genetic Algorithm for Integrated Scheduling and Routing Optimization in Smart Manufacturing

An Incremental Planning Strategy-Based Genetic Algorithm for...

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International Conference on Control and Automation (ICCA)

作者： Jiarong Yao Yao Guo Jiangpeng Li Rong Su Keck Voon Ling Boon Siew Han Hong Yee Alvin Wong School of Electrical and Electronic Engineering Nanyang Technological University Singapore Centre for Advanced Robotics Technology Innovation (CARTIN) School of Electrical and Electronic Engineering Nanyang Technological University Singapore Schaeffler Hub for Advanced Research (SHARE@NTU) Nanyang Technological University Singapore

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

Production scheduling has always been an important topic in smart manufacturing especially integrated with dispatching and routing of automatic guided vehicle or autonomous mobile robots, which is generally modeled as a nondeterministic polynomial-hard integer programming problem. However, most existing studies solve this combinatorial optimization problem through decomposition, namely dealing with scheduling and routing separately, or just assuming a fixed predefined distance matrix for routing, which sacrifices the solution quality for shorter time of decision making. As for metaheuristic solution for such integrated models, the need for effective and efficient searching rules is urgent, so that the heuristics can be more fit for specific purpose and scenarios. Thus, in this paper, an integrated scheduling and routing model is proposed oriented towards the optimization of production scheduling and fleet management in smart manufacturing environment. A genetic algorithm (GA) is used to solve this problem based on incremental planning (IP) strategy which makes effect through ensemble of two local search operators considering the time windows and alternative paths for every transportation task of AGVs. The effectiveness of the proposed method is validated through a simulation case study with horizontal comparison. Results showed that the IP strategy can improve the solution quality and traffic load imbalance of the factory layout, by reducing the makespan and working time of AGV by about 11.5% and 9% respectively. About 80% of the tasks obtained a shorter makespan by adopting an alternative path, showing the ability of traffic load balancing among layout elements when the problem scale increases.

关键词： Job shop scheduling Layout Telecommunication traffic Routing Dispatching Planning IP networks

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