A 3-D flexible vision system for robotic assembly cell: an artificial intelligence based approach

1995 ◽  
Author(s):  
H. Najjari
2021 ◽  
Vol 101 (3) ◽  
Author(s):  
Korbinian Nottensteiner ◽  
Arne Sachtler ◽  
Alin Albu-Schäffer

AbstractRobotic assembly tasks are typically implemented in static settings in which parts are kept at fixed locations by making use of part holders. Very few works deal with the problem of moving parts in industrial assembly applications. However, having autonomous robots that are able to execute assembly tasks in dynamic environments could lead to more flexible facilities with reduced implementation efforts for individual products. In this paper, we present a general approach towards autonomous robotic assembly that combines visual and intrinsic tactile sensing to continuously track parts within a single Bayesian framework. Based on this, it is possible to implement object-centric assembly skills that are guided by the estimated poses of the parts, including cases where occlusions block the vision system. In particular, we investigate the application of this approach for peg-in-hole assembly. A tilt-and-align strategy is implemented using a Cartesian impedance controller, and combined with an adaptive path executor. Experimental results with multiple part combinations are provided and analyzed in detail.


Author(s):  
Nidhi Rajesh Mavani ◽  
Jarinah Mohd Ali ◽  
Suhaili Othman ◽  
M. A. Hussain ◽  
Haslaniza Hashim ◽  
...  

AbstractArtificial intelligence (AI) has embodied the recent technology in the food industry over the past few decades due to the rising of food demands in line with the increasing of the world population. The capability of the said intelligent systems in various tasks such as food quality determination, control tools, classification of food, and prediction purposes has intensified their demand in the food industry. Therefore, this paper reviews those diverse applications in comparing their advantages, limitations, and formulations as a guideline for selecting the most appropriate methods in enhancing future AI- and food industry–related developments. Furthermore, the integration of this system with other devices such as electronic nose, electronic tongue, computer vision system, and near infrared spectroscopy (NIR) is also emphasized, all of which will benefit both the industry players and consumers.


2014 ◽  
Vol 898 ◽  
pp. 763-766
Author(s):  
Zhi Hao Li

The research and application of artificial intelligence has a very wide range in intelligent robot field. Intelligent robot can not only make use of artificial intelligence gain access to external data, information, (such as stereo vision system, face recognition and tracking, etc.), and then deal with it so as to exactly describe external environment, and complete a task independently, owing the ability of learning knowledge, but also have self-many kinds of artificial intelligence like judgment and decision making, processing capacity and so on. It can make corresponding decision according to environmental changes. Its application range is expanding. In deep sea exploration, star exploration, mineral exploration, heavy pollution, domestic service, entertainment clubs, health care and so on, the figure of intelligent robots artificial intelligence application can all be seen.


Author(s):  
Jian Liu ◽  
J. P. Sadler

Abstract A flexible robotic assembly cell is described, and some of the research activities involving the cell and robot applications in manufacturing environments are presented. This research relies heavily on computer simulation. Assembly cell computer modeling, cell calibration, robot collision detection, and off-line programming are described in this paper.


Author(s):  
Alec R. Miller ◽  
Raymond J. Cipra

Abstract This paper examines the development of a networked simulation system. The Automated Robotic Manipulation (ARM) simulator is a central part of the network. This simulation tool currently assists with research and education into automated assembly. Robots, fixtures, conveyors, and parts create an automated assembly cell which is used to test advanced manufacturing software. ARM animates models of these physical components and enhances them with additional forms of three-dimensional graphical visualization. The feasibility of automated assembly can rapidly be assessed from the visual content presented by the simulator. Input formats for ARM are flexible enough to support a wide range of assembly cells and activities. Files and network transmissions customize the simulator to a particular assembly cell and its activities. The emerging assembly data protocol promotes the development of a truly integrated manufacturing system. A graphical interface complete with multiple views assists assembly cell layout and activity review, and networked operations significantly expand its role to areas such as interactive robot control and assembly preview.


2020 ◽  
Vol 4 (3) ◽  
pp. 95
Author(s):  
Sotiris Makris ◽  
Kosmas Alexopoulos ◽  
George Michalos ◽  
Andreas Sardelis

This paper investigates the feasibility of using an agent-based framework to configure, control and coordinate dynamic, real-time robotic operations with the use of ontology manufacturing principles. Production automation agents use ontology models that represent the knowledge in a manufacturing environment for control and configuration purposes. The ontological representation of the production environment is discussed. Using this framework, the manufacturing resources are capable of autonomously embedding themselves into the existing manufacturing enterprise with minimal human intervention, while, at the same time, the coordination of manufacturing operations is achieved without extensive human involvement. The specific framework was implemented, tested and validated in a feasibility study upon a laboratory robotic assembly cell with typical industrial components, using real data derived from a car-floor welding process.


Robotica ◽  
1991 ◽  
Vol 9 (1) ◽  
pp. 31-42 ◽  
Author(s):  
Dae-Won Kim ◽  
Bum-Hee Lee ◽  
Myoung-Sam Ko

SUMMARYIn this paper, an approach to modelling of a robotic assembly cell is proposed and a method for managing the cell operation is described using a knowledge base. Since the modelling structure is based on the concept of the state variable, the relationships between states are described by the state transition map (STM). The knowledge-bases for state transition and assembly job information are obtained from the STM and the assembly job tree (AJT), respectively. Using the knowledge-base, the System structure is discussed in relation to both managing the cell operation and evaluating the performances. Finally, a simulation algorithm is presented with the simulation results to show the significance of the proposed modelling approach.


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