Robot Navigation in Dynamic Environments
The task of navigating, that is, moving from one place to another in any kind of environment, is an extremely easy task for humans. Robots on the other hand, barely perceive the world, which is formidably complex and process this limited data to plan their motions. One can argue that on simple scenarios, the task of navigating is completely solved. Nonetheless, full autonomy in robotics has not arrived yet. This is a key aspect for the future deployment of robots in order to be a mainstream technology adopted by society, either if robots are mobile platforms, autonomous cars, flying quadcopter, etc.
In this talk, I will present an overview of my work on robot navigation on dynamic environments. Under the interaction with pedestrians, complex situations arise where known path planning techniques provide poor solutions. I will present a new prediction approach on human motion and how to integrate it under the same planning scheme, obtaining a more intelligent robot motion behavior.
Still, some degree of uncertainty is unavoidable, due to the unpredictable nature of pedestrians, making impossible a perfect accuracy on prediction. Hence, I will discuss on how to calculate plans on adversarial scenarios, leveraged by probability distributions, as an effective way to avoid potentially dangerous situations