In a world where automation of processes is more and more on demand, machine vision is continuously, explored to address several industrial problems such as quality inspection. In the processed-food industry where the...
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ISBN:
(纸本)9781424425945
In a world where automation of processes is more and more on demand, machine vision is continuously, explored to address several industrial problems such as quality inspection. In the processed-food industry where the external quality attributes of the product are inspected visually before the packaging line, machine visionsystems often involve the extraction of a larger number of features than those actually needed to ensure proper quality control. This work experiments with several feature selection techniques in order to reduce the number of attributes analyzed by a real-time vision-based food inspection system, Four filter-based and wrapper-based feature selectors are evaluated on seeded buns and tortillas datasets. Experimental results show that consistency-based and the RELIEF subset evaluation techniques perform the best for all the considered datasets in terms of accuracy However, variations in the number of attributes selected still vary significantly between these techniques.
An overview is presented of the research and development aspect of a major project on intelligent sensor-based robot systems. A description is given of the results on tactile sensing using: a force-optical technique, ...
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An overview is presented of the research and development aspect of a major project on intelligent sensor-based robot systems. A description is given of the results on tactile sensing using: a force-optical technique, integration of such a sensor into a gripper finger, video rate stereo-vision processing, VLSI implementation of novel vision architectures, an inference imaging device using the SHADOW technique, and highly adaptive self-tuned control.
The importance of robotics has been recognized by the manufacturing industry. The introduction of Computer vision has greatly increased the versatility and application domain of robots such as the interaction between ...
The importance of robotics has been recognized by the manufacturing industry. The introduction of Computer vision has greatly increased the versatility and application domain of robots such as the interaction between the robot and its changing environment. From previously developed vision position correction methods and currently used visual servo-feedback techniques, computer visionsystems present many possibilities in improving the quality and productivity of an industrial product. But computer visionsystems also have limits in dealing with some robotic tasks such as Storage Battery Cap Installation. Random geometric distortion exists, which results from the characteristics of battery material or from the positioning error of fixtures. robotic teaching-playback method can not guarantee the assembly precision when deviation happens. A vision system introduced into the robotic system allows it to respond to an uncertain environment. Conventional vision correction methods only drive robots to the final position without considering robotic trajectory control. They reduce the robotic operation speed compared with stable conditions. Visual servo-feedback techniques can generate the optimal path and assembly precision, but the calculation of visual servo control.algorithm is time consuming. It also reduces robotic execution time. In addition, random assembly tasks sometimes do not need vision correction. So the justification of this roboticvision system is improved robotic assembly accuracy that does not affect other robot performance. In this thesis a new roboticvisioncontrol.system, Automatic vision Switching System (AVSS), was designed. It was derived from the concept of Just-in-Timeand dealt with the installation of storage battery caps. It demonstrated a vision system that functions to correct just when it is needed. Image processing techniques for solving the battery hole's centroid values were included in AVSS design. The experiment was carried out based on a
The potential of additive methods to integrate with machine learning (ML) models in hybrid manufacturing is significant in developing closed-loop processes for intelligent and adaptive control. This study presents a f...
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The potential of additive methods to integrate with machine learning (ML) models in hybrid manufacturing is significant in developing closed-loop processes for intelligent and adaptive control. This study presents a framework to defect mitigation that leverages a hybrid deep convolutional neural network (CNN) architecture with laser powder bed fusion additive systems. It connects on-site optical vision and sensor streams to identify process abnormalities and report real-time remedial actions. The hybrid CNN automatically connects reported anomalies to the physical actuation where quality issues might occur in a closed-loop fashion. This enables self-learning and autonomous corner-cutting while offering a pathway to new applications in digital manufacturing, such as surface finish optimisation and shape adaptation within a single build. In a case study, we demonstrate that our framework enables inspection and control.at a level never seen before, as demonstrated by its precision in product inspection with an F-score of 93.8% and its ability to adjust control.at a frequency exceeding 10 Hz. This work not only enables new learning paradigms for the development of real-time control.systems for hybrid manufacturing, but also accelerates the process of AI-driven intelligent manufacturing by equipping industrial production systems with intelligence, flexibility and resilience. Our technique for tight coupling of process signals and actuation is a significant technical breakthrough in this critical pathway.
Due to legal changes, the use of agents for soil disinfection in arboriculture is severely limited. For this reason, tree nurseries must look for new ways in which weed control.can be earned out on seed beds in the fu...
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ISBN:
(纸本)9781510663411
Due to legal changes, the use of agents for soil disinfection in arboriculture is severely limited. For this reason, tree nurseries must look for new ways in which weed control.can be earned out on seed beds in the future. In cooperation with the local Chamber of Agriculture we want to explore the use of Unmanned Aerial Vehicles (UAVs) for the autonomous weed detection and weed management in arboriculture to develop an innovative approach for weed control. UAVs are selected becauseofthe disadvantage of ground-based roboticsystems m agriculture which is the limitation of their usability in wet soils, as most roboticsystems get stuck and are no longer manoeuvrable. Climate change is causmg these weather conditions to occur more frequently. This paper evaluates early research results of a vision-based crop row detection system for UAV-based weed detection in arboriculture in regards to overall detection performance, real-time capability, weight, size and power-consumption. 2023 SPIE.
The authors present an overview of the research and development being carried as part of a major project on intelligent sensor-based robot systems. Results are reported on tactile sensing using a force-optical techniq...
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The authors present an overview of the research and development being carried as part of a major project on intelligent sensor-based robot systems. Results are reported on tactile sensing using a force-optical technique, the integration of such a sensor into a gripper finger, video-rate stereo vision processing, VLSI implementation of a novel vision architecture, inference imaging device using SHADOW technique, and highly adaptive self-tuned control. The system ultimately will incorporate twin-camera-head stereo vision, range finding, and intelligent tactile processing.
This paper describes the proposal and implementation of two camera sensor system used in combination with SCARA robot for sorting process control. Theoretical basics of 3D camera sensor evaluation and options for mutu...
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ISBN:
(纸本)9783037856031
This paper describes the proposal and implementation of two camera sensor system used in combination with SCARA robot for sorting process control. Theoretical basics of 3D camera sensor evaluation and options for mutual camera placement are included. The paper is focused on sensor system components selection and implementation specifics for particular robotic system as well. Sensor system uses OMRON vision Mate control.er for basic image recognition and PC for resulting data processing of specific points three dimensional position calculation.
A description is given of the Independent Agents Architecture, designed for building behavior-based robots which make use of sophisticated, computationally expensive, sensory modalities. systems built using this archi...
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ISBN:
(纸本)081862163X
A description is given of the Independent Agents Architecture, designed for building behavior-based robots which make use of sophisticated, computationally expensive, sensory modalities. systems built using this architecture have three layers corresponding to perception, behavior, and motor control. The use of a shared perception layer prevents unnecessary redundancy in the processing of sensor data. robotic tasks are decomposed into independent stimulus/response behaviors, each of which is implemented by a separate agent. The formalism of stimulus/response spaces is introduced to model these sensorimotor behaviors. This formalism provides a method to analyze when behavioral systems will be free from potential action conflicts. In addition, it is demonstrated that it is possible to build a robotic system which performs dynamic tasks through the use of qualitative sensorimotor behaviors instead of mathematical models of the physical world. Juggler, a behavior-based balloon-bouncing robot, is an example of such a system.
The development of multi-sensor based flexible assembly cells will increase substantially the scope of applications of manipulators in industry. This paper is concerned with the development of a multi-sensor assembly ...
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