the most popular method for optimizing a certain strategy based on a reward is Reinforcement Learning (RL). Lately, a big challenge for this technique are computer games such as StarCraft II which is a real-time strat...
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the most popular method for optimizing a certain strategy based on a reward is Reinforcement Learning (RL). Lately, a big challenge for this technique are computer games such as StarCraft II which is a real-time strategy game, created by Blizzard. the main idea of this game is to fight between agents and control objects on the battlefield in order to defeat the enemy. this work concerns creating an autonomous bot using reinforced learning, in particular, the Q-Learning algorithm for playing StarCraft. JamesBot consists of three parts. State Manager processes relevant information from the environment. Decision Manager consists of a table implementation of the Q-Learning algorithm, which assigns actions to states, and the epsilon-greedy strategy, which determines the behavior of the bot. In turn, Action Manager is responsible for executing commands. Testing bots involves fighting the default (simple) agent built into the game. Although JamesBot played better than the default (random) agent, it failed to gain the ability to defeat the opponent. the obtained results, however, are quite promising in terms of the possibilities of further development.
3D Move To See (3DMTS) is a mutli-perspective visual servoing method for unstructured and occluded environments, like that encountered in robotic crop harvesting. this paper presents a deep learning method, Deep-3DMTS...
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3D Move To See (3DMTS) is a mutli-perspective visual servoing method for unstructured and occluded environments, like that encountered in robotic crop harvesting. this paper presents a deep learning method, Deep-3DMTS for creating a single -perspective approach for 3DMTS through the use of a Convolutional Neural Network (CNN). the novel method is developed and validated via simulation against the standard 3DMTS approach. the Deep-3DMTS approach is shown to have performance equivalent to the standard 3DMTS baseline in guiding the end effector of a robotic arm to improve the view of occluded fruit (sweet peppers): end effector final position within 11.4 mm of the baseline;and an increase in fruit size in the image by a factor of 17.8 compared to the baseline of 16.8 (avg.). (C) 2019, IFAC (international Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.
the paper proposes three Gain-Scheduling (GS) control design approaches dedicated to the position control of electromagnetic actuated clutch systems. the initial nonlinear mathematical model of the plant is simplified...
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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 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 a solution for sowing maize using an autonomous robot. the robotic seeder minimizes human involvement in the sowing process and hence reduces errors, time consumption and increases efficiency. An a...
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ISBN:
(纸本)9781450372350
this paper presents a solution for sowing maize using an autonomous robot. the robotic seeder minimizes human involvement in the sowing process and hence reduces errors, time consumption and increases efficiency. An adjustable feature has been introduced which can be used to adjust the width of the seeder by considering the width of seedbeds in the fields. the robot is equipped with a 2D laser scanner and a seed sowing mechanism. the sensor provides environmental information in the form of distance data which is desired for controlling the movement of the seeder. the information is further used to extract seedbeds using Random Sample Consensus (RANSAC) with line fitting. For autonomous navigation, differential drive and PID control have been implemented. the sowing mechanism allows accurate seed sowing in proper alignment. It drops seeds continuously on equidistant positions during movement of the seeder. A simulated field using V-Rep has been created for testing the functionality of the seeder in simulation. the results from simulation present trajectories of the autonomous seeder and seeds sowing pattern. A hardware prototype is also presented showing the proposed seeder.
the purpose of this study was to develop an expert system that recommends types of plants that help remove toxic substances to improve air quality in a given ***, it is usually horticultural experts who suggest the ri...
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ISBN:
(纸本)9781450372640
the purpose of this study was to develop an expert system that recommends types of plants that help remove toxic substances to improve air quality in a given ***, it is usually horticultural experts who suggest the right plants as per the environment, where feasible. there is also a significant gap in research related to any such smart systems as revealed in the literature *** led to the creation of the Plant Recommender Expert System (PRES) - an intelligent system that accesses expert knowledge by utilizing a set of inputs (e.g. expected humidity, average temperature, etc.) to recommend the type(s) of plants that should be purchased to suit the conditions of any given *** to office environments within the United Arab Emirates (UAE), PRES was successfully evaluated using several case studies with known outcomes.
Radio communication in Indonesia has developed quite well. However there are still many problems in the use of radio frequency channels although actually it has been regulated by the government. Radio channels for mer...
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this article briefly summarizes the theory of chaos and its applications. Firstly, we begin by describing chaos as an aperiodic bounded deterministic motion, which is sensitive to initial states and therefore unpredic...
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Tulip crop production in the Netherlands suffers from severe economic losses caused by virus diseases such as the Tulip Breaking Virus (TBV). Infected plants which can spread the disease by aphids must be removed from...
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Tulip crop production in the Netherlands suffers from severe economic losses caused by virus diseases such as the Tulip Breaking Virus (TBV). Infected plants which can spread the disease by aphids must be removed from the field as soon as possible. As the availability of human experts for visual inspection in the field is limited, there is an urgent need for a rapid, automated and objective method of screening. From 2009-2012, we developed an automatic machine vision based system, using classical machine learning algorithms. In 2012, the experiment conducted a tulip field planted at production density of 100 and 125 plants per square meter, resulting in images with overlapping plants. Experiments based on multispectral images resulted in scores that approached results obtained by experienced crop experts. the method, however, needed to be tuned specifically for each of the data trails, and a NIR band was needed for background segmentation. Recent developments in artificial intelligence and specifically in the area of convolutional neural networks, allow the development of more generic solutions for the detection of TBV. In this study, a Faster R-CNN network is applied on part of the data from the 2012 experiment. the outcomes show that the results are almost the same compared to the previous method using only RGB data. (C) 2019, IFAC (international Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.
In this paper a fuzzy inference system in fuzzy toolbox package in MATLAB using two “fuzzified” control parameters for the fixed point transformation-based adaptive controller is applied for the strongly dynamic non...
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ISBN:
(数字)9781728156255
ISBN:
(纸本)9781728156262
In this paper a fuzzy inference system in fuzzy toolbox package in MATLAB using two “fuzzified” control parameters for the fixed point transformation-based adaptive controller is applied for the strongly dynamic non-linear system, the “van der Pol Oscillator”. the paper presents a comparison of the operation of the classical controller and a novel one combined with fuzzy inference system.
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