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Although it may seem incredible to you, robotic devices can now be accurately configured to manipulate minuscule objects to carry out testing on an unfathomable scale. These tiny objects are picked up using a vacuum or suction device and are presented individually to the robotic system for analysis. These machines carry out intricate tasks human beings just can’t undertake.
Summation of Parts
It is quite clear that this level of intricacy is coming to the forefront of how these machines are applied in the lab. As my previous articles have shown, the objectives of these systems are varied, with some applications very unfamiliar to the lay person. Fundamental to how these machines work, is their ability to perceive their environment and interact with objects in it. Acquiring an image and then interpreting the image in a meaningful way are two of the principle objectives for modern-day robotics. But none of this is possible without the correct lighting, as it is needed to enhance the objects around, allowing the machine to interpret them with more accuracy. Dim lit laboratories are not ideal environments for these automated machines, with them instead being better suited to optimum lighting environments.
This interpretation and analysis of objects is where specific elements are being sought out using various specialized techniques. Windowing is often used as a means of concentrating the analysis of a particular device upon a small area in an attempt to conserve resources, especially the time taken to execute jobs. This is one of the most effective approaches to analysing objects in an environment and is related to other premises discussed in earlier articles on this website. The act of identifying a shape is accomplished by undertaking various techniques such as template matching and shape approximation.
Detecting the outer surface of an object can be using simple logic flow diagrams as way of determining the overall shape of an object. As might already know, inspection tasks are a primary part of any robotic system used in lab automation. These tasks are described as feature specific but they often involve operations or the role of repeating tasks over and over. When making judgemental inspection decisions, humans still trump robotics every time but this may not always be the case. Lab automation is a significant application for this type of device, especially inspection, identification, and of course component insertion. The possibilities do seem to be endless in regards to this subject, so watch this space to find out more on these exciting developments.
When we think of lab automation systems, we think of systems that are capable of inspecting elements but their suitability to carry out such tasks depends on a number of factors. Someone once asked me whether or not a robot would be capable of carrying out the final inspection of experimental product. This proved to be a difficult question to answer, as it is unclear whether automated machines can be decisive when evaluating the final stage of an experiment. In fact I would say that at present this technology is certainly not capable of such feats but who knows what their capabilities may be in the future.
I would still trust a human operative over a robotic one when it comes to making these kinds of decisions. Perhaps in situations where there a few obvious anomalies with the final product, a detection system or inspection device could be used to quality assure the product. In manufacturing environments, such a system could be used to detect parts that were missing from the product or broken pieces that had been damaged during the manufacturing process. These tasks are highly suitable for this system and there are many benefits to using inspection systems in this way. The process is normally carried out by human operatives who seem to fall short when executing this task, often missing defects or anomalies. This is why this role needs to be carried out by robotic systems and this is also why companies have spent so much money developing this technology.
The question needs to be answered; why is it human operatives are unable to adequately carry out inspection work? It seems to be the repetition of this task causes the human brain to effectively tune out, making it increasingly more likely they will miss any defects or missing parts. In a similar way to how a word processor works, a machine can perform a search of a document to find a single word in a few seconds. This is a task that may take a human operative hours but there are no guarantees that the word will be found. A human operative has difficulty fully focusing when the task is of a repetitive nature but a machine can handle this task without any issues. Even if a human being could manage to achieve this task, the role would be so boring that they most certainly would quit. This is before taking into account how hazardous such a job may be to the operative, with eye strain being a common issue.
Following the identification of a window of interest, analysis is carried out to target certain features in the lab. Threshold analysis is often described as transcribing an image to black and white pixels. This not a new approach by any means but it is still considered one of the most affective forms of analyzing images. The main reason why this was so popular in the infant days of machine visioning was due to its ability to screen out the sensing systems operational variability.
The threshold approach is used in many binary systems, though these systems are not limited to a singular threshold method. If you consider the problem of identifying a snake which is grey in colour, on a black and white tiled floor for example. This approach would simply portray the image as being a black snake on a white floor, with no tiles visible at all. Maybe the automated system in question does not need to worry about this but other systems will and therefor a solution was needed. In a laboratory setting, two thresholds are set select the gray part of an image and allow the device to pick-up just that part. For this very reason, threshold systems are designed to accept two distinct thresholds, allowing the system to get around the problems outlined above. If only one threshold is required, the other threshold can be tuned to one extreme of the brightness scale, leaving that threshold completely void.
The act of finding the perfect threshold value for a binary visioning system is a key process in creating a successful vision automation system. This problem is much trickier than you may think, with many external variables affecting the outcome. Selecting a threshold that lays exactly half-way between the two light extremes can lead to a totally dark image, if both thresholds are below mid-range. Some sort of intelligent approach must be adopted to select the required threshold. Where this intelligence comes from is entirely up to the designer of the project but some sort of manual input from a human operator may be required. Although computer programs have improved greatly in how they calculate these ranges, they are still not up to the task completely. This does, however leave a system that is not fully automated and therefore cannot be classed as an automated device as such.
As you can see, there are many issues with this approach but most of these can be overcome with a little planning and design.
Programming an automated machine requires a skillset that not many people possess and therefore people with these particular abilities are very much in demand. If you study the articles posted on this website, you will gain a foundation level knowledge on this subject and be in a position to pursue more in-depth training.
Most computer programs include an editor, a compiler and a simulator for testing the programs in a virtual test environment. The editor is used to input the code and make amendments to the code but you can also use the keyboard to execute commands. Comments can be placed strategically within the code to help other programmers understand what the code does and why it is there. Most programming languages terminate each execution with a semi-colon but this is not true for all. This software is used primarily for controlling lab automation machines and other industrial robotics. These types of automated machine use x, y and z co-ordinates to navigate around their surroundings. There may also be an additional rotational access that needs to be factored into this motion logic.
The units for the Cartesian axes are as follows:
- x axis: millimeters
- y axis: millimeters
- z axis: millimeters
- r axis: degrees
The first programming procedure that needs to be carried out, is to configure the various location points that are to be used by the software. The location pendant and keyboard are used to input this data in the system. I will use an example to demonstrate how this feature works. Once the teach pendant, the robotic manipulator and axis orientation are in their default positions, this position is recorded as the starting point position. There will be a program instruction generated to signify this operation.
It the required axis points are pre-determined or are already stored in one of the variables, the automation machine can be instructed to move to that predetermined position. The variable name for this location is entered between parentheses. This move can also be represented as an arithmetic expression which includes computational axis co-ordinates relating to a particular position.
Ordinarily there is a safe clearance distance programmed into the software for the z-axis, allowing the picker or gripper to position itself just above the pick-up point. A positive z-axis offset is required to prevent the device from damaging the item it is trying to interact with. If need be, it is possible to execute a move along only one axis using a special command which only uses co-ordinates from one axis. In fact, it is frequently necessary to move along the z-axis only and usually a special command is created for this process. All that is required is a destination point to be entered between the parentheses in the command and the machine will automatically motion towards those co-ordinates.
This is a very basic view of how motion is achieved using robotics and in truth, there is a lot more to it than what has been highlighted here. This article is part of a series of articles on this subject which will help my readers gain a better understanding of robotics and automation.
I would just like to take this opportunity on this historic day, to welcome everyone to my new website. This promises to be a blog like no other and one that can be used as a valuable source of information for those interested in technological advancements. We will provide our visitors with something unique and something that can’t be found on any other web source.
I have worked as a software engineer in the lab automation industry and have seen huge changes in how this industry has evolved, in terms of its willingness to adopt an online approach. Machines in the laboratory historically store their data on local media which can only be accessed from the lab vicinity. This has many limitations in how users can access the test data and process it, limitations which cost the industry hundreds of thousands of pounds each year.
We live in an era where we can access our pictures, e-mails and videos from anywhere in the world, yet those accessing lab data have to be on site to gain access. Given that most large chemical agencies have offices all over the world, this makes it very hard for teams from different areas to collaborate on the same projects. Each company really needs a secure web portal where scientists can gain access data and discuss that data on a shared medium.
This is where the world of lab automation meets the world of web-design. Developing web solutions that help increases the availability of these machines is essential in a world where more and more people are working together in diverse locations. Using protocols and programming languages that securely achieve our goals is a must. This website looks at many ways in which this can be achieved and what was once thought of as science fiction could very soon become science fact.
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