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Design and Develop a Vertical Box Smart Farm based on Programmable Logic controller 9

Design and Develop a Vertical Box Smart Farm based on Progra...

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9th IEEE international conference on Advanced robotics and Mechatronics (ICARM)

作者： Tummawai, Thananop Prakhummin, Peeraput Ledkaew, Kittisak Phongsatja, Anocha Lunsungyang, Witayakorn Sukpancharoen, Somboon Khon Kaen Univ Dept Mech Engn Khon Kaen 40002 Thailand Khon Kaen Univ Dept Automat Robot & Intelligent Syst Khon Kaen 40002 Thailand Khon Kaen Univ Dept Agr Engn Khon Kaen 40002 Thailand

ISBN: (纸本)9798350385731;9798350385724

Agriculture plays an indispensable role in daily life, and presently, soilless cultivation techniques such as hydroponics enjoy widespread popularity. In efforts to advance this methodology, we have implemented a sophisticated Programmable Logic controllers (PLCs) system tailored for Nutrient Film Technique (NFT) hydroponic cultivation within a greenhouse setting. This system incorporates a diverse array of sensors designed to measure crucial parameters including water temperature, Electrical Conductivity (EC), and Potential of Hydrogen ion (pH) levels. The PLCs is meticulously programmed to oversee and regulate the entire cultivation process seamlessly. Additionally, integration of a Raspberry Pi facilitates Internet of Things (IoT) functionalities, thereby enhancing convenience and enabling remote monitoring capabilities. We aim to conduct a comparative analysis between two distinct greenhouse systems: one under the control of the PLC, and the other devoid of such automated control, in order to discern and evaluate the disparities in plant growth and development between them. The study focuses on key variables such as canopy width and leaf count of Green Oak Lettuce over a 5-week period, with the primary environmental factors influencing these variables being the levels of EC and pH in the nutrient solution. The findings of this study will provide valuable insights into the benefits of environmental control in greenhouse-based hydroponic cultivation of green oak lettuce, contributing to the advancement of sustainable and efficient agricultural practices.

关键词： Hydroponics

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The Grasp Reset Mechanism: An Automated Apparatus for Conducting Grasping Trials

The Grasp Reset Mechanism: An Automated Apparatus for Conduc...

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IEEE international conference on robotics and Automation (ICRA)

作者： DuFrene, Kyle Nave, Keegan Campbell, Joshua Balasubramanian, Ravi Grimm, Cindy Oregon State Univ Collaborat Robot & Intelligent Syst CoRIS Inst Corvallis OR 97331 USA Southwest Res Inst SwRI San Antonio TX 78238 USA

ISBN: (纸本)9798350384581;9798350384574

Advancing robotic grasping and manipulation requires the ability to test algorithms and/or train learning models on large numbers of grasps. Towards the goal of more advanced grasping, we present the Grasp Reset Mechanism (GRM), a fully automated apparatus for conducting large-scale grasping trials. The GRM automates the process of resetting a grasping environment, repeatably placing an object in a fixed location and controllable 1-D orientation. It also collects data and swaps between multiple objects enabling robust dataset collection with no human intervention. We also present a standardized state machine interface for control, which allows for integration of most manipulators with minimal effort. In addition to the physical design and corresponding software, we include a dataset of 1,020 grasps. The grasps were created with a Kinova Gen3 robot arm and Robotiq 2F-85 Adaptive Gripper to enable training of learning models and to demonstrate the capabilities of the GRM. The dataset includes ranges of grasps conducted across four objects and a variety of orientations. Manipulator states, object pose, video, and grasp success data are provided for every trial.

关键词： Manipulators

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An Aaptive Sliding Mode control Based on an Improved Reduced-Order Proportional-Integral Observer with an Improved Super-Twisting Oserver 6

An Aaptive Sliding Mode Control Based on an Improved Reduced...

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6th international conference on robotics, intelligent control and Artificial Intelligence, RICAI 2024

作者： Peng, Bo Shen, Jiandong Sun, Qing Huang, Ying School of Automation Xi'an University of Posts and Telecommunications Xi'an China

ISBN: (纸本)9798331541699

This paper describes an adaptive sliding mode control method, which constructs an improved over-twisted observer based on the improved reduced-order proportional integral observer (IROPIO) and Super-Twisting linear term over-twisting algorithm (STLT). Among them, the system introduces a first-order linear term, which accelerates the convergence rate of velocity estimation and greatly reduces the estimation error. At the same time, this method effectively reduces the fluctuation of the control signal and shortens the time required for the system trajectory to reach the slip mode surface. IROPIO can accurately predict unknown disturbances when the system is running, and provide feedforward compensation for adaptive sliding mode control (ASMC), effectively solving the overshoot condition of the speed response that may occur due to disturbance estimation errors during the speed jump process. Robustness and dynamic performance are thus improved. Experimental results show that this method can significantly optimize control performance in practical applications, providing an efficient and reliable solution to the control problems of high-speed and high-precision systems. © 2024 IEEE.

关键词： Sliding mode control

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Force-Limited control of Wave Energy Converters using a Describing Function Linearization 15

Force-Limited Control of Wave Energy Converters using a Desc...

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15th IFAC conference on control Applications in Marine Systems, robotics and Vehicles, CAMS 2024

作者： McCabe, Rebecca Haji, Maha N. Sibley School of Mechanical and Aerospace Engineering Cornell University IthacaNY14853 United States

Actuator saturation is a common nonlinearity. In wave energy conversion, force saturation conveniently limits drivetrain size and cost with minimal impact on energy generation. However, such nonlinear dynamics typically demand numerical simulation, which increases computational cost and diminishes intuition. This paper instead uses describing functions to approximate a force saturation nonlinearity as a linear impedance mismatch. In the frequency domain, the impact of controller impedance mismatch (such as force limit, finite bandwidth, or parameter error) on electrical power production is shown analytically and graphically for a generic nondimensionalized single degree of freedom wave energy converter in regular waves. Results are visualized with Smith charts. Notably, systems with a specific ratio of reactive to real mechanical impedance are least sensitive to force limits, a criteria which conflicts with resonance and bandwidth considerations. The describing function method shows promise to enable future studies such as large-scale design optimization and co-design. © 2024 Elsevier B.V.. All rights reserved.

关键词： Linearization

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intelligent Pursuit and Evasion Decision-Making in Active Defense Scenarios 6

Intelligent Pursuit and Evasion Decision-Making in Active De...

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6th international conference on robotics, intelligent control and Artificial Intelligence, RICAI 2024

作者： Chen, Yutong Yang, Zhen Zhang, Bao Wang, Xingyu Zhang, Yuhe Zhou, Deyun School of Microelectronics Northwestern Polytechnical University Shaanxi Xi'an China School of Electronics and Information Northwestern Polytechnical University Shaanxi Xi'an China

ISBN: (纸本)9798331541699

In the complex environment of modern aerial warfare, an attacking missile attempts to successfully penetrate defenses and strike a target aircraft, while a defensive missile intercepts the attacking missile to protect the target. Meanwhile, the target aircraft itself possesses intelligent evasion capabilities, employing smart maneuvering strategies to evade the attacking missile's pursuit. In this triadic confrontation within an active defense scenario, intelligent strategy decisions of all participating agents are critical to the outcome of the engagement. In the dynamically evolving battlefield, improving the penetration capability of the attacking missile, enhancing the coordination of multi-agent decision-making, and strengthening the evasion capability of the target aircraft are key challenges. To address these challenges, the objective of this study is to enhance the attacking missile's penetration ability in an active defense scenario, particularly in the presence of interference from a defensive missile, while also improving the coordination and collaborative effectiveness of multiple agents. Therefore, this work proposes an improved Multi-Agent Proximal Policy Optimization (MAPPO) algorithm that incorporates a Transformer Encoder. By introducing the Transformer Encoder, the algorithm's representation capacity and decision-making precision are significantly enhanced, addressing the limitations of traditional MAPPO in processing complex environmental information, penetrating defensive missiles, and generating intelligent evasion strategies for the target aircraft. © 2024 IEEE.

关键词： Aircraft accidents

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Utilizing Cloud Solutions for Object Recognition in the Context of Industrial robotics Sorting Tasks 18

Utilizing Cloud Solutions for Object Recognition in the Cont...

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18th international conference on Innovations in intelligent Systems and Applications (INISTA)

作者： Stefan, Ioana Livia Mateescu, Andrei Vlasceanu, Ioana Miruna Popescu, Dragos Constantin Sacala, Ioan Stefan Univ Politehn Bucuresti Fac Automat Control & Comp Automat Control & Syst Engn Dept Splaiul Independentei 313 Bucharest 060042 Romania Extreme Light Infrastruct ELI NP Str Reactorului 30 Bucharest 077125 Magurele Romania Horia Hulubei Natl Inst R&D Phys & Nucl Engn IFIN Str Reactorului 30 Bucharest 077125 Magurele Romania

ISBN: (纸本)9798350368130

The rapid advancements in sectors such as Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), networking and cloud computing are opening the opportunity for integrating these techniques with robots from the manufacturing field, with the promising perspective of improved performance at reduced costs, inspiring the new field of cloud robotics. In this paper, we propose an architecture for integrating industrial robots with Cloud AI object recognition services. For our proposed solution, we explore the results obtained by simulating a sorting task in RobotStudio, communicating with Microsoft Azure Custom Vision API by sending the web service calls from a computer running a Python script. We present the cycle time added by the communication with the cloud service and test the robustness of the system by comparing the results obtained with four sets of images: unaltered, altered with gaussian noise, barrel distortion and both.

关键词： RobotStudio industrial robots Cloud object recognition Azure Custom Vision computer vision

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Offline Goal-Conditioned Reinforcement Learning for Safety-Critical Tasks with Recovery Policy

Offline Goal-Conditioned Reinforcement Learning for Safety-C...

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IEEE international conference on robotics and Automation (ICRA)

作者： Cao, Chenyang Yan, Zichen Lu, Renhao Tan, Junbo Wang, Xueqian Tsinghua Shenzhen Int Grad Sch Ctr Intelligent Control & Telesci Shenzhen Peoples R China

ISBN: (纸本)9798350384581;9798350384574

Offline goal-conditioned reinforcement learning (GCRL) aims at solving goal-reaching tasks with sparse rewards from an offline dataset. While prior work has demonstrated various approaches for agents to learn near-optimal policies, these methods encounter limitations when dealing with diverse constraints in complex environments, such as safety constraints. Some of these approaches prioritize goal attainment without considering safety, while others excessively focus on safety at the expense of training efficiency. In this paper, we study the problem of constrained offline GCRL and propose a new method called Recovery-based Supervised Learning (RbSL) to accomplish safety-critical tasks with various goals. To evaluate the method performance, we build a benchmark based on the robot-fetching environment with a randomly positioned obstacle and use expert or random policies to generate an offline dataset. We compare RbSL with three offline GCRL algorithms and one offline safe RL algorithm. As a result, our method outperforms the existing state-of-the-art methods to a large extent. Furthermore, we validate the practicality and effectiveness of RbSL by deploying it on a real Panda manipulator. Code is available at https://***/Sunlighted/***.

关键词： Self-supervised learning

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Multimodal Object Query Initialization for 3D Object Detection

Multimodal Object Query Initialization for 3D Object Detecti...

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IEEE international conference on robotics and Automation (ICRA)

作者： van Geerenstein, Mathijs R. Ruppel, Felicia Dietmayers, Klaus Gavrila, Dariu M. Robert Bosch GmbH Corp Res D-71272 Renningen Germany Delft Univ Technol Intelligent Vehicles Grp Delft Netherlands Ulm Univ Inst Measurement Control & Microtechnol Ulm Germany

ISBN: (纸本)9798350384581;9798350384574

3D object detection models that exploit both LiDAR and camera sensor features are top performers in large-scale autonomous driving benchmarks. A transformer is a popular network architecture used for this task, in which so-called object queries act as candidate objects. Initializing these object queries based on current sensor inputs is a common practice. For this, existing methods strongly rely on LiDAR data however, and do not fully exploit image features. Besides, they introduce significant latency. To overcome these limitations we propose EfficientQ3M, an efficient, modular, and multimodal solution for object query initialization for transformer-based 3D object detection models. The proposed initialization method is combined with a "modality-balanced" transformer decoder where the queries can access all sensor modalities throughout the decoder. In experiments, we outperform the state of the art in transformer-based LiDAR object detection on the competitive nuScenes benchmark and showcase the benefits of input-dependent multimodal query initialization, while being more efficient than the available alternatives for LiDAR-camera initialization. The proposed method can be applied with any combination of sensor modalities as input, demonstrating its modularity.

关键词： Benchmarking

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Lite-HRPE: A 6DoF Object Pose Estimation Method for Resource-limited Platforms 18

Lite-HRPE: A 6DoF Object Pose Estimation Method for Resource...

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IEEE 18th international conference on control and Automation (ICCA)

作者： Liu, Xin Guan, Qi Xue, Shibei Zhao, Dezong Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Shanghai Engn Res Ctr Intelligent Control & Manag Shanghai 200240 Peoples R China Univ Glasgow James Watt Sch Engn Glasgow G12 8QQ Lanark Scotland

ISBN: (纸本)9798350354416;9798350354409

Accurately estimating the six-degree-of-freedom pose of objects is essential for intelligent robotics. Although significant progress has been made in this area, most studies fail to account for specific hardware limitations for model deployment, which remains a major challenge for resource-constrained scenarios. To address this issue, we propose Lite-HRPE, a lightweight RGB-based pose estimation method, which leverages a multi-branch parallel structure to extract spatial and semantic information of key points for pose estimation. Additionally, Lite-HRPE adopts the G-block and G-neck modular structure and streamlines the original feature extraction network to realize a compact network structure. This allows Lite-HRPE to strike a balance between pose estimation accuracy, parameter count, computational load, and runtime speed. Our evaluation on public datasets shows that Lite-HRPE achieves a 95.7% accuracy with only 10.8% of the number of parameters and 11.8% of the FLOPs compared to Hybridpose.

关键词： Semantics

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Towards Sustainable Cyber-Physical Manufacturing Systems 22

Towards Sustainable Cyber-Physical Manufacturing Systems

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22nd IFAC conference on Technology, Culture and international Stability (TECIS)

作者： Brennan, Robert W. Lyu, Guolin Univ Calgary Calgary AB T2N 1N4 Canada

We propose a self-managing services architecture for automated manufacturing systems to enable sustainable manufacturing operations. The architecture utilises both software agents and IEC 61499 function blocks to realise manufacturing systems that quickly respond to change while maintaining stable system operation and efficient use of available resources. To explore the system's ability to adapt to disturbances, a stochastic agent-based simulation of the automated manufacturing system with random equipment failures was developed. The results of the simulation demonstrate that the proposed self-managing services architecture is capable of rapidly reconfiguring part routings in order to reduce work in progress and maintain stable system operation. Copyright (C) 2024 The Authors.

关键词： Artificial Intelligence and Applications intelligent Systems and Applications Sustainable Design and control

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