Robot movement control is a complex ordeal and costly, especially in terms of time, resources, and material, and wear of parts is a common drawback. Maitools s imulator is a cost-efficient tool for defining robots, environments, and tasks. Maitools main focus lies on the software, instead the hardware. Its autonomous control solution enables the robot, no matter which type, to learn and optimize its movement, manage environmental variables, and this significantly helps in minimizing development costs.
Maitools allows to conveniently enter the part specifications, setting components, and target values of the robot. In regard to the complex nature of the definition of a robot, this process takes place locally on your PC or laptop.
Execute the learning and send the data to the cloud, where the learning process takes place, because of the required high-spec computing resource.
Take advantage of all the benefits:
Maitools and Maicloud is a two-step-solution to support robot development.
Cost-efficient and time-saving. For beginners, professionals and businesses alike.
· The URDF or GUI-type input box to enter the part's specifications, components, and target values are provided.
· Choose from a list of basic parts most commonly used.
· The platform is made with a Java-based rich client platform (RCP) for easy use on a PC.
· A 3-D screen is used to easily set up robot tasks.
· Output range of each part's specification is converted into training-data.
· The data is transferred into the AI-engine.
·The robot learns, what the most efficient movements are.
· Benefit from a variety of algorithms to find the optimal motion for specific tasks.
· First, the robot learns the capabilities of its components, and second, it learns to process a specific task.
· As a client, you are provided with a display to monitor various cloud computing settings and learning processes.
· After the learning process is completeted or if it is still ongoing, an API- or ROS-package is offered to transmit the virtually acquired data so that learning can be continued in the real robot.
· Extraction of the data after the task is completed.