3 accepted papers
Sampling-based model predictive control (MPC) is experiencing a resurgence in robotics following both recent hardware successes and advancements in parallelized physics simulation. However, to build on this progress, the robotics community needs to develop shared tools for prototyping, benchmarking,…
We present a unified framework for solving trajectory optimization problems in a derivative-free manner through the use of sequential convex programming. Traditionally, nonconvex optimization problems are solved by forming and solving a sequence of convex optimization problems, where the cost and co…
We demonstrate the surprising real-world effectiveness of a very simple approach to whole-body model- predictive control (MPC) of quadruped and humanoid robots: the iterative linear-quadratic regulator (iLQR) algorithm with MuJoCo dynamics and finite-difference approximated derivatives. Building upo…