Blog on Robot Control Programming

To do meaningful tasks, a robot needs to be programmed to go through its motion cycle. A manipulator's path in space, along with auxiliary activities to support the work cycle, can be described as a robot programmed. Opening and closing the gripper, making rational decisions, and interacting with other pieces of equipment in the robot cell are a few examples of peripheral tasks. Programming a robot involves inserting the orders into its controller memory. Different robots enter commands in a variety of ways.

The ability of these robots to adapt to real-time changes, despite their immense power and complexity, cannot be compared to that of humans, especially given the surrounding environment. Robots can mimic the human senses' adaptability to welding environments by analyzing the context and relevant characteristics, such as problem diagnosis, fault repair, and robotic motion path. This user dependence is unmatched. To increase the automation of the robots, some operator who modifies the input is required. To make the robots more automated, this reliance on user input must be reduced. Due to this robotic welding's rigidity, there are numerous difficulties that must be overcome, such as joint seam tracking and joint weld

Robot control System:

Types of Robot Programming:

Nearly all industrial robots today and in the near future have digital computers acting as their controllers and compatible storage devices acting as their memory units.

Three different programming techniques may be identified for these robots: Programming through leadership, computer-like robot programming languages, and offline programming are the three options.

1.   Lead through programing:

The two approaches for inserting commands into computer memory that are most frequently used today are lead-through programming and robot language programming.

When a job is taught to a robot via lead-through programming, the manipulator is moved through the necessary motion cycle while the programmed is simultaneously stored in the controller memory for future replay.

The lead-through teach procedure can be executed in one of two ways:

a)    Manual Lead through programming:

b)    Powered Lead through Programming:

Advantages:

1.simple to learn

2.Knowledge of computer programming is not required of the coder.

Disadvantages:

1.Leadthrough programming causes the robot cell or production line to be offline.

2.Modem computer-based technologies like CAD/CAM, production data bases, and local communications networks are not easily compatible with this approach.

 

2. Offline Programming

Applications

Robotic Welding:

Due to the availability of sensor-based characteristics for directing the robots in welding operations, which is an excellent technological advancement, robotic welding has been able to replace physical welding in hostile environments with high temperatures and gas vapors. Advancement Industrial robots are mostly utilized in high-capacity manufacturing and GMAW, or gas metal arc welding. As robotic welding has become more popular, it has become necessary to have improved problem identification and repair skills as well as greater ability to control welding settings and robotic movements.

Robotic welding is a highly developed form of automated welding in which welders still maintain control and oversight of the operation. Robotic technology enables accurate and speedy outcomes, less waste, and more safety.

The ability of these robots to adapt to real-time changes, despite their immense power and complexity, cannot be compared to that of humans, especially given the surrounding environment. Robots can mimic the human senses' adaptability to welding environments by analyzing the context and relevant characteristics, such as problem diagnosis, fault repair, and robotic motion path. This user dependence is unmatched. To increase the automation of the robots, some operator who modifies the input is required. To make the robots more automated, this reliance on user input must be reduced. Due to this robotic welding's rigidity, there are numerous difficulties that must be overcome, such as joint seam tracking and joint weld detection.

Various steps in welding

1)    The preparation phase: begins with the machine operator properly arranging the components that will be welded. Then, he or she sets up all the equipment, including the robot's programmed, the robot itself, the power source, the electrode wires that will be used, and the gas that will be used. The welding operation's parameters are then put up by him or her. Then, a pre-program is accessed and brought online using offline programming such as CAD. The robotic welding may therefore only need minor calibration adjustments, which the welder operator can easily make by performing an online simulation of the desired procedure.

 

2)    Welding Phase: Automatic welding equipment must be able to perform welding tasks equally well as physical welding equipment, including tracking seams, changing welding parameters in real-time, and maintaining torch orientation that follows desired trajectory (which may differ from predetermined trajectory).

3)    Analysis Phase: The operator examines the finished product in the analysis phase, which comes after welding, to determine whether it is satisfactory or whether changes to the first two phases are necessary. Thanks to contemporary sensors like 3D laser cameras, this step is finished online at the same time as the welding phase.

Types of Robotic welding

1)    Welding seam tracking technology:

Due to errors in machining, assembly, and weld deformation brought on by uneven temperature fields, the weld's location and configuration change. The technology of seam tracking is used to view the welding status in real time throughout the operation in order to modify the weld.

Currently, sensor and control technology are the mainstays of weld seam tracking technique. In the welding robot sector, sensor applications are changing from single sensors to multisensory intelligent information fusion. It is common practice to investigate the seam of the weld monitoring method from a control perspective using hybrid and fuzzy approaches to control.

The combination of these technologies gives the seam weld tracking technology stronger command features including adaptability and self-learning.

2)    Digital Twinning:

An offline playback or real-time rendering of telemetry obtained from a remote system constitutes a digital twin. Digital twins don't operate hardware, but they do offer useful information on actual motion versus requested motion. Predictive analytics, AI training, decision-making, augmented reality (AR) engagement, and teleoperation all benefit greatly from this data. 

Digital twins have a wide range of possible uses, including processes like part manufacturing, assembly, testing, palletizing, robotic manipulation, and much more. When machining a part, it is possible to visualize the machining operations from the raw material to the finished part by using a digital twin rendering of the actual hardware motion. A digital twin is a crucial tool for comparative analysis when employing a robot for additive or subtractive manufacturing because the system's repeatability can suffer for a number of reasons.

If a manufacturing process involves robots, the tasked motion sequences can be compared to and validated using a digital twin simulation of the robot work cell that uses the real motion generated by the hardware. This is significant since many automotive work cells use multiple robot systems that collaborate closely. Keep in mind that many unarticulated systems that use digital twins may also be controlled or altered by robotic systems that may also use digital twins to highlight the breadth of potential uses for this technology