In traditional robot programming, the robot movement must be programmed with predefined waypoint which the robot has to move through. This is tedious, requires a lot thinking, creates movement which are not always optimal and makes the robot cell very inflexible and intolerant to changes. These problems increase even more when objects have variable positioning which is very often the case with vision enabled robot cells such as bin picking.
Real time dynamic motion planning removes the above-mentioned challenges. The motion planner uses CAD and/or 3D point cloud as input to understand the environment. Based on this it will calculate the optimal movement for the robot on the fly. In the case of bin picking for instance, this means that the robot finds the optimal path per cycle. In the future with human-robot applications, the robot will continuously adapt the movement of the human and plan its path accordingly.
This demonstration shows the value of global dynamic motion planning in agile production by lowering the time it takes to make changes to the setup and making complex robot motions possible. The cell consist of with multiple bins, and each bin and the environment in general is flexible and can change during the operation. This has the following advantages:
Advantages to the user:
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 825196