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MinorNet: A Lightweight neural network for battlefield scene classification 14

MinorNet: A Lightweight neural network for battlefield scene...

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14th International symposium on computational intelligence and Design, ISCID 2021

作者： Guo, Shi Ni, Yong Xing, Ke Liu, Yang Ni, Wei Jiangsu Automation Research Institute Lianyungang China

ISBN: (纸本)9781665438568

Computer vision has a wide range of applications, and the current demand for intelligent battlefields is increasing. However, most research on CNN (Convolutional Neural Network) models did not consider both accuracy and lightweight. To achieve an efficient neural network model for battlefield scene classification, we propose a lightweight and efficient neural network named the MinorNet. The design of MinorN et refers to the advantages and avoids the shortcomings of the previous models. Min bottleneck is an essential part of Minor Net. The Min bottleneck contains Depthwise Separable Convolution, channel shuffle, linear transformation, and residual part. They can further improve model capabilities and efficiency without increasing inference computation. This paper establishes a novel dataset named battlefield scene dataset of 7 different kinds of a real battlefield scenes. As a result, our MinorNet achieves 88.3% with only 2.4M parameters in the battlefield scene dataset, being about 0.5x smaller yet still more accurate 3.7% than the previously most commonly used lightweight place classification model. © 2021 ieee.

关键词： Neural network models

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On-line force capability evaluation based on efficient polytope vertex search

On-line force capability evaluation based on efficient polyt...

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ieee International Conference on Robotics and automation (ICRA)

作者： Skuric, Antun Padois, Vincent Daney, David Univ Bordeaux Bordeaux INP CNRS UMR 5218 AuctusInriaIMS F-33405 Talence France

ISBN: (纸本)9781728190778

Ellipsoid-based manipulability measures are often used to characterize the force/velocity task-space capabilities of robots. While computationally simple, this approach largely approximate and underestimate the true capabilities. Force/velocity polytopes appear to be a more appropriate representation to characterize the robot's task-space capabilities. However, due to the computational complexity of the associated vertex search problem, the polytope approach is mostly restricted to offline use, e.g. as a tool aiding robot mechanical design, robot placement in work-space and offline trajectory planning. In this paper, a novel on-line polytope vertex search algorithm is proposed. It exploits the parallelotope geometry of actuator constraints. The proposed algorithm significantly reduces the complexity and computation time of the vertex search problem in comparison to commonly used algorithms. In order to highlight the on-line capability of the proposed algorithm and its potential for robot control, a challenging experiment with two collaborating Franka Emika Panda robots, carrying a load of 12 kilograms, is proposed. In this experiment, the load distribution is adapted on-line, as a function of the configuration dependant task-space force capability of each robot, in order to avoid, as much as possible, the saturation of their capacity.

关键词： Geometry Force measurement Trajectory planning Conferences Force Robot control Tools

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3D biped locomotion control including seamless transition between walking and running via 3D ZMP manipulation

3D biped locomotion control including seamless transition be...

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ieee International Conference on Robotics and automation (ICRA)

作者： Sugihara, Tomomichi Imanishi, Kenta Yamamoto, Takanobu Caron, Stephane Preferred Networks Inc Chiyoda Ku 1-6-1 Otemachi Tokyo Japan Osaka Univ Grad Sch Engn 2-1 Yamadaoka Suita Osaka Japan ANYbotics AG Hagenholzstr 83a CH-8050 Zurich Switzerland CNRS UM LIRMM Montpellier France

ISBN: (纸本)9781728190778

A novel control scheme for biped robots to manipulate the ZMP three-dimensionally apart from the actual ground profile is presented. It is shown that the linear invertedpendulum-like dynamics with this scheme can represent a wider class of movements including variation of the body height. Moreover, this can also represent the motion in aerial phase. Based on this, the foot-guided controller proposed by the authors is enhanced to enable the robots to locomote on highly uneven terrains and also to seamlessly transition between walking and running without pre-planning the overall motion reference. The controller guarantees the capturability at landing and defines the motion by a time-variant state feedback, which is analytically derived from a model predictive optimization. It is verified through some computer simulations.

关键词： Legged locomotion State feedback Solid modeling Three-dimensional displays computational modeling Dynamics Predictive models

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Emergent Hand Morphology and control from Optimizing Robust Grasps of Diverse Objects

Emergent Hand Morphology and Control from Optimizing Robust ...

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ieee International Conference on Robotics and automation (ICRA)

作者： Pan, Xinlei Garg, Animesh Anandkumar, Animashree Zhu, Yuke NVIDIA Santa Clara CA 95051 USA Univ Calif Berkeley Berkeley CA 94720 USA Univ Toronto Vector Inst Toronto ON Canada CALTECH Pasadena CA 91125 USA Univ Texas Austin Austin TX 78712 USA

ISBN: (纸本)9781728190778

Evolution in nature illustrates that the creatures' biological structure and their sensorimotor skills adapt to the environmental changes for survival. Likewise, the ability to morph and acquire new skills can facilitate an embodied agent to solve tasks of varying complexities. In this work, we introduce a data-driven approach where effective hand designs naturally emerge for the purpose of grasping diverse objects. Jointly optimizing morphology and control imposes computational challenges since it requires constant evaluation of a black-box function that measures the performance of a combination of embodiment and behavior. We develop a novel Bayesian Optimization algorithm that efficiently co-designs the morphology and grasping skills through learned latent-space representations. We design the grasping tasks based on a taxonomy of human grasp types: power grasp, pinch grasp, and lateral grasp. Through experimentation and comparative study, we demonstrate that our approach discovers robust and cost-efficient hand morphologies for grasping novel objects.

关键词： Costs Taxonomy Morphology Optimization methods Grasping Robot sensing systems Hardware

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An extension to the NK fitness landscape model to study pleiotropy, epistasis, and ruggedness independently

An extension to the NK fitness landscape model to study plei...

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ieee symposium Series on computational intelligence (SSCI)

作者： Priyanka Mehra Arend Hintze Department of MicroData Analytics Dalarna University Falun Sweden BEACON Center for the Study of Evolution in Action Michigan State University East Lansing USA

ISBN: (纸本)9781665487696

The NK model is designed to study evolutionary adaptation in rugged fitness landscapes. The factor $K$ determines the number of interacting genes, their degree of pleiotropy and epistasis, and consequently the ruggedness of the fitness landscape. However, in natural organisms, the degree of epistatic interactions and the number of functions a gene can have are to a certain degree determining the ruggedness of the landscape. Still, pleiotropy and epistasis can evolve independently from each other, and are to some degree independent of the ruggedness of the landscape. Here, we propose an extension to the standard NK model to investigate these factors independently of each other. Over the course of evolution the computational model organisms can now change how their genes interact and how they control phenotypic traits. Further, the degree of epistasis and pleiotropy is affected by the ruggedness of the landscape and becomes reduced with increasing ruggedness. While this proves that the extension of the model performs as expected, the adaptations are minor, presumably because only relatively short periods of adaptations with few mutations can be studied.

关键词： Adaptation models computational modeling Organisms Standards computational intelligence

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Distributed Motion Coordination Using Convex Feasible Set Based Model Predictive control

Distributed Motion Coordination Using Convex Feasible Set Ba...

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ieee International Conference on Robotics and automation (ICRA)

作者： Zhou, Hongyu Liu, Changliu Noweigian Univ Sci & Technol Dept Marine Technol NO-7491 Trondheim Norway Carnegie Mellon Univ Inst Robot 5000 Forbes Ave Pittsburgh PA 15213 USA

ISBN: (纸本)9781728190778

The implementation of optimization-based motion coordination approaches in real world multi-agent systems remains challenging due to their high computational complexity and potential deadlocks. This paper presents a distributed model predictive control (MPC) approach based on convex feasible set (CFS) algorithm for multi-vehicle motion coordination in autonomous driving. By using CFS to convexify the collision avoidance constraints, collision-free trajectories can be computed in real time. We analyze the potential deadlocks and show that a deadlock can be resolved by changing vehicles' desired speeds. The MPC structure ensures that our algorithm is robust to low-level tracking errors. The proposed distributed method has been tested in multiple challenging multi-vehicle environments, including unstructured road, intersection, crossing, platoon formation, merging, and overtaking scenarios. The numerical results and comparison with other approaches (including a centralized MPC and reciprocal velocity obstacles) show that the proposed method is computationally efficient and robust, and avoids deadlocks.

关键词： Roads System recovery Prediction algorithms Stability analysis Robustness Real-time systems Trajectory

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A Real-Time Multi-Task Framework for Guidewire Segmentation and Endpoint Localization in Endovascular Interventions

A Real-Time Multi-Task Framework for Guidewire Segmentation ...

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ieee International Conference on Robotics and automation (ICRA)

作者： Zhou, Yan-Jie Liu, Shi-Qi Xie, Xiao-Liang Zhou, Xiao-Hu Wang, Guan-An Hou, Zeng-Guang Li, Rui-Qi Ni, Zhen-Liang Fan, Chen-Chen Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China CAS Ctr Excellence Brain Sci & Intelligence Techn Beijing 100190 Peoples R China Macau Univ Sci & Technol Inst Syst Engn CASIA Must Joint Lab Intelligence Sci & Technol Macau Peoples R China

ISBN: (纸本)9781728190778

Real-time guidewire segmentation and endpoint localization play a pivotal role in robot-assisted minimally invasive surgery, which is helpful to reduce radiation dose and procedure time. Nevertheless, the tasks often come with the challenge of limited computational resources. For this purpose, a real-time multi-task framework with two stages is developed. In the first stage, a Fast Attention-fused Network (FAD-Net) is proposed to obtain accurate guidewire segmentation masks. In the second stage, a lightweight localization network and a post-processing algorithm are designed to robustly predict the guidewire endpoint position. Quantitative and qualitative evaluations on intraoperative X-ray sequences from 30 patients demonstrate that the developed framework outperforms the previously-published results for the tasks, achieving state-of-the-art performance. Moreover, the inference rate of the developed framework is approximately 10.6 FPS, which meets the real-time requirement of X-ray fluoroscopy. These results indicate the proposed approach has the potential to be integrated into the robotic navigation framework for endovascular interventions, enabling robotic-assisted minimally invasive surgery.

关键词： Location awareness Minimally invasive surgery Navigation Prediction algorithms Real-time systems Robustness Inference algorithms

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Energy Efficient Smart Outdoor Lightning System Using SCADA control System 3

Energy Efficient Smart Outdoor Lightning System Using SCADA ...

引用

3rd International Conference on Intelligent Computing, Instrumentation and control Technologies, ICICICT 2022

作者： Kumar, P. Marish Abhishek Dheeven, T. Department of Electrical and Electronics Engineering Chennai India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

The late twentieth century is actively working to conserve electrical energy. Street lights are vital;however they are expensive, consequently, there is a need to manage the system so that it becomes economical while also conserving energy adequately. Manually operating the street lights is a time-consuming and labor-intensive task. For this endeavor, we were inspired to create a street light monitoring system via automation, that could vastly exceed present street light control techniques. Because street lights are now handled continuously, there is a moderate waste of energy and effort. Using our technique, street lights may be turned on and off automatically, allowing us to adjust the intensity and energy consumption. This waste is also seen in places with low traffic at night where street lights are being used unsustainably. Our method guarantees that using a light-dependent resistor (LDR) and an infrared sensor (IR sensor), we can measure the density of traffic in the vicinity of the outdoor brightness and even the luminosity of ambient brightness in the immediate neighborhood, and use both data to control the street light's using SCADA function. © 2022 ieee.

关键词： Monitoring

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On the Democratization of Machine Learning Pipelines

On the Democratization of Machine Learning Pipelines

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ieee symposium Series on computational intelligence (SSCI)

作者： Alexandre Carqueja Bruno Cabral João Paulo Fernandes Nuno Lourenço University of Porto DEI-FEUP Porto Portugal University of Coimbra CISUC DEI-FCTUC Coimbra Portugal University of Porto LIACC DEI-FEUP Porto Portugal

ISBN: (纸本)9781665487696

With the increase of Machine Learning (ML) adoption throughout many industries, the need for efficient methods to continuously design, develop, and deploy ML models has also grown. To address this issue, several ML pipelines have emerged with the goal of creating development environments which facilitate the deployment, evaluation and maintenance. In this paper, we advocate that most existing pipelines are not well suited for the initial stages of ML development, due to their high setup and maintenance overheads. As such, we propose a lightweight Quick Machine Learning framework, QML, which is capable of reducing the setup overhead and operating in the low infrastructure environments that are most common-place in experimental ML projects. To demonstrate QML's usefulness, we present a case-study where a lightweight ML pipeline was developed, and subsequently validated on a standard ML classification problem. Lastly, we assess the differences between our pipeline and an alternative lightweight workflow, based on DAGsHub. With this comparison, we conclude that our approach increases ML task automation as well as feature support, while falling short only in the Experiment Tracking category. To enable the broader community to experiment and assess QML, as well as the Lightweight Pipeline, this project has been made publicly available 1 1 https://***/WALEX2000/qml1 https://***/WALEX2000/qml1 https://***/WALEX2000/qml1 https://***/WALEX2000/qml

关键词： Industries automation Design methodology Pipelines Machine learning Maintenance engineering Task analysis

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Eigenvector of Gram-Matrix based Open-Fault Diagnosis Method for Two-level Three-Phase Inverter

Eigenvector of Gram-Matrix based Open-Fault Diagnosis Method...

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International Conference on Power Electronics and Motion control (IPEMC)

作者： Yang Zhou Jin Zhao Yang Liu Lijun Sun Ministry of Education School of Artificial Intelligence and Automation Key Laboratory of Imaging Processing and Intelligence Control Huazhong University of Science and Technology Wuhan China China Electronic Product Reliability and Environmental Testing Research Institute Guangdong Provincial Key Laboratory of Electronic Information Products Reliability Technology Guangzhou China

ISBN: (数字)9798350351330

ISBN: (纸本)9798350351347

This paper studies the power switch open-circuit(OC) fault in two-level three-phase (2L3P) voltage source inverter (VSI). According to the topological symmetry of the inverter, when it works in healthy conditions, its phase currents are standard sine waves with only 120-degree phase difference, and the similarity between phase currents is high. When OC fault occurs, the current waveforms of both normal and fault phases will be distorted, the similarity will be changed. Therefore, this paper introduces the Gram matrix in image processing to measure the similarity and proposes a fast and computationally efficient diagnostic method based on the eigenvector of Gram-Matrix. Physical experiment shows that both single-switch fault and multiple-switch fault on the same leg can be effectively detected and located.

关键词： Legged locomotion Fault diagnosis Voltage source inverters Switches computational efficiency Maintenance Velocity measurement

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