Today, industries have understood the benefits of automation. They help themselves by using new technologies. As a result, robots are more present than ever in the production processes of many different industries.
However, robots are efficient in very simple tasks only. They are based on classic programming which needs to define rules and templates. In practice, there are still a lot of situations where there are too many parameters to be considered. Thus, the definition of rules becomes too complex for classically programmed robots.
This reduces drastically the opportunities of automation brought by robots, if no other technology is supporting them.
Fortunately, artificial intelligence is able to learn from complex tasks on its own. After having studied a specific task, AI can understand the situation it sees. Then, it identifies all the different steps to perform the task and in order to reach its objective.
At the same time, the AI system communicates the actions the robotic arm needs to make. Hence, the robot can perform the task automatically, no matter its complexity.
Ciseo is a company specialized in the design and manufacturing of machines in the pharmaceutical industry.
This client wanted to build an intelligent gripper system to automate loading and unloading processes in the production chain.
Sagacify built an artificial intelligence agent to optimize the gripper system for Ciseo. It helps the robot in dealing with complex situations. More precisely, it tells him which object to move or to take, in the right order, in order to avoid flipping anything over or hitting other objects.