In this episode, Abate De Mey interviews Guido De Croon about Evolutionary Robotics and its use to design behaviors for flying robots. The DelFly UAV robot learns to fly through an open window when trapped inside a room thanks to a controller optimized using a Genetic Algorithm over several generations, similar to natural evolution. The controller is programmed using a Behavior Tree Framework, which is more intuitive and adaptable than the traditional Neural Network framework. This helps the user to manually adapt the controller to handle the differences between the simulation and the real world. They go on to discuss the challenges and benefits of using Evolutionary Robotics to learn robot behaviors.
Video of the Evolutionary Robotics strategy used to develop a controller for the DelFly robot:
Scheper, K. Y., Tijmons, S., de Visser, C. C., & de Croon, G. C. (2015). Behavior Trees for Evolutionary Robotics. Artificial life. Vol 21, issue 1.
Guido De Croon
Guido de Croon is Assistant Professor at the Micro Air Vehicle lab of Delft University of Technology in the Netherlands. His research interest lies with computationally efficient algorithms for robot autonomy, with a particular focus on computer vision and evolutionary robotics.
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- Guido de Croon’s Website
- “Behavior Trees for Evolutionary Robotics”