Roberto Calandra PRO
Full Professor at TU Dresden. Head of the LASR Lab. Working in AI, Robotics and Touch Sensing.
Roberto Calandra
Facebook AI Research
JSM - 01 July 2019
From YouTube: https://www.youtube.com/watch?v=g0TaYhjpOfo
Robotics still heavily rely on human expertise !
On one hand, it is unfeasible to hand-design general purpose controllers
On the other hand, there is mistrust for automatic design of controllers
Policy (i.e., parametrized controller)
Action executed
Learning a controller is equivalent to optimizing the parameters of the controller
Current state
Parameters of the policy
Bio-inspired Bipedal Robot "Fox":
[Calandra, R.; Seyfarth, A.; Peters, J. & Deisenroth, M. P. Bayesian Optimization for Learning Gaits under Uncertainty Annals of Mathematics and Artificial Intelligence (AMAI), 2015, 76, 5-23]
Not Symmetrical (about 5° difference). Why?
Because it is walking in a circle!
Simulated hexapod:
Question: can we move beyond standard single-objective BO?
[Yang, B.; Wang, G.; Calandra, R.; Contreras, D.; Levine, S. & Pister, K. Learning Flexible and Reusable Locomotion Primitives for a Microrobot IEEE Robotics and Automation Letters (RA-L), 2018, 3, 1904-1911]
[Liao, T.; Wang, G.; Yang, B.; Lee, R.; Pister, K.; Levine, S. & Calandra, R. Data-efficient Learning of Morphology and Controller for a Microrobot IEEE International Conference on Robotics and Automation (ICRA), 2019]
Two levels of optimization
(instead of a single bigger optimization)
Future challenges:
Thank you for your time
By Roberto Calandra
Designing and tuning controllers for real-world robots is a daunting task which typically requires significant expertise and lengthy experimentation. Bayesian optimization has shown to be a successful approach to automate these tasks with little human expertise required. In this talk, I will discuss the main challenges of robot learning, and how BO helps to overcome some of them. Using as showcase real-world applications where BO proved to be effective, I will also discuss how the challenges encountered in robotics applications can guide the development of new BO algorithms.
Full Professor at TU Dresden. Head of the LASR Lab. Working in AI, Robotics and Touch Sensing.