We show how an end goal can be demonstrated to a Robot and then left to complete the task even when there a multiple start points in the task
We show how a robot can complete a task when given an end goal by a human to strive for. This opens the doors for flexible and rapid programming of robot for flexible packaging of goods.
We demonstrate how a task can be tracked using Vision based AI Algorithms. The technique we are using does not require too rigid setups making it very adaptable to various settings. This technique can be used to create a digital thread and record of a manual process.
We demonstrate how a task can be tracked using Vision based AI Algorithms. The technique we are using does not require too rigid setups making it very adaptable to various settings. This technique can be used to create a digital thread and record of a manual process.
In this video, we show our architecture that is capable of enabling a collaborative robot to infer a human's action and support the assembly task that a human is carrying out.
Here we show how an Unmanned Aerial Vehicle could autonomously land on a moving platform using only visual information to track the moving platform and make decisions.
Here we develop a medium fidelity immersive environment model of an actual factory. We made use of medium fidelity in order to ensure that real time computation is possible within time constraints and to ensure that users derive full benefits of the immersive environment without lags. We applied a combination of Laser point cloud, drawings and field studies to obtain the dimensions of the artefacts in the factory as well as the factory itself.
Here we develop an immersive environment model of an actual factory. Using cutting edge computer logic, we connected a Discrete Event Simulator to the immersive environment. This enabled us to be able to visualise material flows and human flow in a factory without actual deployment. This saves costs in terms of rework and also enables engineers to explore alternative processes that could be more efficient without actual deployment in the real world.
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