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The Future Of Robotics Is Fuzzy

The Future Of Robotics Is Fuzzy

  • Robotics using fuzzy logic will be a game-changer for flexible robotic production.

Robotics is not an AI problem, it is an engineering problem. The innovators in this space are trying to solve the issue of how to make robots move autonomously, and have behavioural control through sensory awareness of their surroundings. Fuzzy Logic Robotics (FLR) recently released a platform that allows customers to go from CAD to control with just one piece of software. 

FLR is working on an “all-in-one” software platform that will make every phase of robotisation easier, from robotic cell design to daily industrial reprogramming by technicians. As per the experts, it creates a virtual environment in which a manufacturing robot may be operated “on the fly” and as easily as a video game.

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FLR is working on an “all-in-one” software platform that will make every phase of robotization more easier, from robotic cell design to daily industrial reprogramming by technicians. As per the experts, it creates a virtual environment in which a manufacturing robot may be operated “on the fly” and as easily as a video game.

Fuzzy Logic

Fuzzy logic has been found to be suitable for applications in robot navigation. This is due to its ability to handle massive amounts of partial and erroneous input signals. Such signal processing could allow robots to navigate in unpredictable surroundings automatically. There has been a lot of research done on the application of fuzzy theory to robot navigation. A common application calls for the robot to be equipped with a variety of sensors for monitoring environmental data. Fuzzification, fuzzy inference, and defuzzification provide decisions that regulate the robot’s behaviour, allowing it to travel autonomously. 

The input to a fuzzy logic controller can come from a variety of sensors. For example, the distance between a robot and obstacles can be detected using ultrasonic sensors. The present position of the robot can be detected using global positioning systems. The ultimate result of fuzzy inference allows a robot to distinguish between distinct contexts and perform the actions requested by the designer.

The following are some of the capabilities accessible in Fuzzy Studio, according to FLR: 

  • With one universal software platform, you can drag and drop CAD parts into the 3D digital twin, automatically build complex trajectories, and deploy them to the production robot in one click. 
  • Fuzzy Studio bridges the gap between simulation and reality, from offline simulation to real-time control, to reduce downtime and optimise the robotics workflow. 
  • No-code real-time digital twin technology was built from the ground up to substantially decrease the need for robotics skills.
  • Easily switch between any robot brand and model with just a few clicks – no need to switch software or redo time-consuming design work. 
  • Even the most sophisticated robotic applications can be handled, and it’s available to businesses of any size.

The majority of robotic and cobotic applications, on the other hand, necessitate complex and disparate software tools as well as brand experts.
Large corporations are showing a lot of interest in the platform. However, in addition to existing users of industrial robots, Fuzzy Logic plans to enter a market still in its infancy: small and medium-sized industrial businesses. The platform eliminates the difficulties of robotic integration and the necessity for robotics knowledge throughout the service life, two constraints that have proved prohibitive for SMEs and SMBs in the past. Already, manufacturers of industrial robotics are increasingly seeing India as a top market for their products. As a result, this new business will undoubtedly shake the Indian robotics sector. In the near future, Indian startups will produce a slew of new products.

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