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Robot navigation in dynamic environments

Robot navigation in dynamic environments


The open workshop of IITP RAS Lab 11 will start

at 17:00 on Friday, September 21, 2018 in room 615.


Speaker: Gonzalo Ferrer.


Short bio: Gonzalo Ferrer completed his PhD thesis in 2015 on robot navigation algorithms in urban environments at the Institut de Robotica i Informatica Industrial IRI, a group inside the Universitat Politecnica de Catalunya (UPC), in Barcelona, Spain.

Before joining Skoltech, Gonzalo worked during two years as a Research Fellow (postdoc) at the APRIL lab. and Intermittent Lecturer in the department of Computer Science and Engineering at the University of Michigan.

Gonzalo has collaborated on international research projects and industry research initiatives, such as the URUS project on human robot cooperation in urban areas or the NGV project in alliance with the Ford Motor Co. on autonomous driving.


In January 2018, Gonzalo joined the Skolkovo Institute of Science and Technology as an Assistant Professor. He will be heading the Mobile Robotics lab., focusing his research on planning, perception and how to combine both into new solutions in robotics.


Abstract: 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.


Everyone is welcome!

17.09.2018 | Сидорова Василина Викторовна


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