Underactuated Robotics: Learning, Planning, and Control for Ecient and Agile Machines Course Notes for MIT 6.832

By Russ Tedrake. 2009

139 citations recorded by the source corpus.

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Citations in the corpus

Weight Agnostic Neural Networks (2019, background): “Unlike the simpler task, it cannot be solved with a linear controller [93, 113].”
Modular Hopping and Running via Parallel Composition (2017, methodology): “We anticipate that templates could be learned from data, in a way that is similar to the search for manipulation primitives / synergies from data Todorov and Ghahramani (2004). We expect that template plants / controllers can then be found by analyzing the reduced-dimensional template dynamics (as d”
Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids (2018, methodology): “This is known as the shooting method in trajectory optimization (Tedrake, 2009).”
The Penn Jerboa: A Platform for Exploring Parallel Composition of Templates (2015, unknown): “Similarly, methods depending on local linearizations of the typically (highly) nonlinear dynamics found in dynamically dexterous locomotion and manipulation systems [3, 4] typically suffer from small basins of attraction [5] and (to our knowledge) high sensitivity to parameters.”
Propagation Networks for Model-Based Control Under Partial Observation (2018, methodology): “This is known as the shooting method in trajectory optimization [28].”
Learning to Predict Without Looking Ahead: World Models Without Forward Prediction (2019, methodology): “As the balance cart-pole task discussed earlier can be trivially solved with a wide range of parameters for a simple linear policy, we conduct experiments where we apply observational dropout on the more difficult swing up cart-pole—a task that cannot be solved with a linear policy, as it requires t”