this paper addresses an autonomous underwater vehicle (AUV) simulator with underwater image sonar and optical vision emulation. Recently, various underwater missions have been automated through the great improvement i...
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ISBN:
(纸本)9788993215151
this paper addresses an autonomous underwater vehicle (AUV) simulator with underwater image sonar and optical vision emulation. Recently, various underwater missions have been automated through the great improvement in underwater image sonar and optical vision technology along with utilization of artificial intelligence. Development of the simulator that emulates underwater image sonar and optical vision can support intelligent underwater missions by visualizing and simulating virtual scenarios and reproducing real missions. In order to benefit from existing software, the presented simulator is based on ROS (Robot Operating System) environment integrated with our image sonar and optical vision emulators. When an underwater virtual scenario of terrain, target objects, and AUVs with sensors is plotted using standard 3-D modeling progams, the simulator configures the scenario and displays sonar and optical images. the ultrasound and light beams arc modeled as a set of rays each, and the image sonar and optical vision are modeled as objects detecting collisions between the rays and target objects at certain positions and orientations. the sonar images generated by the simulator are compared with real images to confirm the validity of the models,
We consider the problem of warehouse multi-robot automation system in discrete-time and discrete-space configuration with focus on the task allocation and conflict-free path planning. We present a system design where ...
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ISBN:
(纸本)9781538695821
We consider the problem of warehouse multi-robot automation system in discrete-time and discrete-space configuration with focus on the task allocation and conflict-free path planning. We present a system design where a centralized server handles the task allocation and each robot performs local path planning distributively. A genetic-based task allocation algorithm is firstly presented, with modification to enable heuristic learning. A semi-complete potential field based local path planning algorithm is then proposed, named the recursive excitation/relaxation artificial potential field (RERAPF). A mathematical proof is also presented to show the semi-completeness of the RERAPF algorithm. the main contribution of this paper is the modification of conventional artificial potential field (APF) to be semi-complete while computationally efficient, resolving the traditional issue of incompleteness. Simulation results are also presented for performance evaluation of the proposed path planning algorithm and the overall system.
It is proposed in this paper the design of a contactless electromagnetic levitation and electrostatic driven rotation control system for a micro mirror. the design can levitate an aluminum micro rotor with 3.3mm diame...
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ISBN:
(纸本)9781538695821
It is proposed in this paper the design of a contactless electromagnetic levitation and electrostatic driven rotation control system for a micro mirror. the design can levitate an aluminum micro rotor with 3.3mm diameter and 8 mu m thickness. Using electromagnetic force and electrostatic force, the rotor can be levitated to 100 mu m height with 20MHz frequency and 0.5A p-p input current and driven to rotate around the vertical axis within the range of +/- 180 degrees. the control system design is presented using detection and control circuit, and the levitation and rotation figures are also presented. the square wave response experiment is carried out to show its feasibility.
Virtual reference feedback tuning (VRFT) and fictitious reference iterative tuning (FRIT) are the data-driven tuning schemes for directly designing feedback controllers. these schemes have been extended to two-degree-...
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ISBN:
(纸本)9781538695821
Virtual reference feedback tuning (VRFT) and fictitious reference iterative tuning (FRIT) are the data-driven tuning schemes for directly designing feedback controllers. these schemes have been extended to two-degree-of-freedom (2DOF) control systems in recent years. the conventional design schemes of 2DOF controllers need a complicated two-stage tuning process. this paper describes a one-stage tuning scheme for the 2DOF control system using a fictitious exogenous signal based on a data-driven method. In the proposed scheme, 2DOF controllers are designed with one criterion, and the least squares method is applied to find the optimal set of 2DOF controller parameters. According to the proposed scheme, the reference models are determined based on the stability margin that is quantified by the sensitivity function. It is also possible to design a control system taking robustness into account. Finally, the effectiveness of the proposed scheme is numerically verified using a simulation example.
this paper addresses the robust cooperative control for lateral formation tracking a set of circles on the given sphere in an absolutely unknown spatial flowfield. Different from the adaptive estimation method for the...
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ISBN:
(纸本)9781538695821
this paper addresses the robust cooperative control for lateral formation tracking a set of circles on the given sphere in an absolutely unknown spatial flowfield. Different from the adaptive estimation method for the unknown flow speed with knowledge of the velocity direction in the literatures, a novel adaptive neural estimate is constructed based on the neighbors' information to approximate the unknown flow velocity. It is noted that such neighbor-based adaptive neural estimation develops the traditional adaptive neural approach by consensus. then, a robust spherical formation tracking control law is established according to flow estimation. the uniform ultimate boundedness is proven when the communication topology associated with networked first-order agents. the effectiveness of the analytical results is verified by numerical simulations.
Small robots have numerous interesting applications in domains like industry, education, scientific research, and services. For most applications vision is important, however, the limitations of the computing hardware...
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ISBN:
(纸本)9781538695821
Small robots have numerous interesting applications in domains like industry, education, scientific research, and services. For most applications vision is important, however, the limitations of the computing hardware make this a challenging task. In this paper, we address the problem of real-time object recognition and propose the Fast Regions of Interest Search (FROIS) algorithm to quickly find the ROIs of the objects in small robots with low-performance hardware. Subsequently, we use two methods to analyze the ROIs. First, we develop a Convolutional Neural Network on a desktop and deploy it onto the low-performance hardware for object recognition. Second, we adopt the Histogram of Oriented Gradients descriptor and linear Support Vector Machines classifier and optimize the HOG component for faster speed. the experimental results show that the methods work well on our small robots with Raspberry Pi 3 embedded 1.2 GHz ARM CPUs to recognize the objects. Furthermore, we obtain valuable insights about the trade-offs between speed and accuracy.
In this paper, the bearing-only formation control problem of multi-agent systems is addressed. the main contributions of the paper are twofold: (1) the local maximal clique graph instead of the global infinitesimal be...
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ISBN:
(纸本)9781538695821
In this paper, the bearing-only formation control problem of multi-agent systems is addressed. the main contributions of the paper are twofold: (1) the local maximal clique graph instead of the global infinitesimal bearing rigidity graph is used to describe the formation configuration;(2) the proposed formation control law is globally stable. To be more specific, by considering the inter-agent communication topology satisfies the maximal clique graph condition, a cost function is designed based on the target formation. Next, the rotation bias of the final formation and the target formation are analyzed. Based on the negative gradient of the cost function, a globally stable distributed controller that only depends on the inter-bearing measurements is proposed and global convergence result and analysis are given. An illustrative example demonstrates the effectiveness and efficiency of the proposed control law.
this paper investigates a method to enhance the performance of the predictive functional control (PFC) using the disturbance observer (DOB). A control method that combines the PFC and DOB has been developed and shown ...
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ISBN:
(纸本)9781538695821
this paper investigates a method to enhance the performance of the predictive functional control (PFC) using the disturbance observer (DOB). A control method that combines the PFC and DOB has been developed and shown to be effective in the past few years. However, there remains room for performance improvement by using a feedforward controller. Here, an approach to improving the tracking performance of the DOB-based PFC is presented by applying feedforward compensation using a zero phase error tracking controller (ZPETC). We provide the detailed background for this approach, and present properties of PFC controllers concerned withthe transfer function representation. To verify the proposed method, we compare it experimentally to DOB-based and standard PFCs. We show that the tracking performance of the proposed method is much better than the other two control methods.
For robotic technology to be adopted within the agricultural domain, there is a need for low-cost systems that can be flexibly deployed across a wide variety of crop types, environmental conditions, and planting metho...
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For robotic technology to be adopted within the agricultural domain, there is a need for low-cost systems that can be flexibly deployed across a wide variety of crop types, environmental conditions, and planting methods, without extensive re-engineering. Here we present an approach for predicting steering angles for an autonomous, crop row-following, agri-robot using only RGB image input. Our approach employs a deep convolutional neural network (DCNN) and an end-to-end learning strategy. We pre-train our network using existing open datasets containing natural features and show that this approach can help to preserve performance across diverse agricultural settings. We also present preliminary results from open-loop field tests that demonstrate the feasibility and some of the limitations of this approach for agri-robot guidance. (C) 2019, IFAC (international Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.
this paper presents the development of a control system for a flexible robot manipulator that can be used in MRI system. In general neurosurgery, real time MR-guide surgical robot is necessary because of the difficult...
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ISBN:
(纸本)9788993215151
this paper presents the development of a control system for a flexible robot manipulator that can be used in MRI system. In general neurosurgery, real time MR-guide surgical robot is necessary because of the difficult operation due to narrow working area and limited field of view. In addition, the MR-compatible flexible robot manipulator has the advantage that it can perform brain tumor surgery accurately and safety. the surgical robot system consists of a flexible manipulator part, a driving part for operating the tool tip, and a control system for robot operation and MR image processing. the MR-compliant flexible manipulator needs a control system because it operates by the tendon drive method using ultrasonic motor and gear. therefore, this paper describes the whole configuration and tele-operation control system of a flexible robot manipulator. we present the results of the experiments using the developed flexible robot manipulator and the force measurement experiment of the tool tip.
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