1 code implementation • 14 Apr 2022 • Spencer M. Richards, Navid Azizan, Jean-Jacques Slotine, Marco Pavone
Real-time adaptation is imperative to the control of robots operating in complex, dynamic environments.
no code implementations • 16 Apr 2021 • Rohan Sinha, James Harrison, Spencer M. Richards, Marco Pavone
We propose a learning-based robust predictive control algorithm that compensates for significant uncertainty in the dynamics for a class of discrete-time systems that are nominally linear with an additive nonlinear component.
1 code implementation • 7 Mar 2021 • Spencer M. Richards, Navid Azizan, Jean-Jacques Slotine, Marco Pavone
Real-time adaptation is imperative to the control of robots operating in complex, dynamic environments.
1 code implementation • 29 Jul 2019 • Sumeet Singh, Spencer M. Richards, Vikas Sindhwani, Jean-Jacques E. Slotine, Marco Pavone
We propose a novel framework for learning stabilizable nonlinear dynamical systems for continuous control tasks in robotics.
1 code implementation • 2 Aug 2018 • Spencer M. Richards, Felix Berkenkamp, Andreas Krause
We demonstrate our method by learning the safe region of attraction for a simulated inverted pendulum.