4 accepted papers
Model-predictive control (MPC) is an increasingly popular method for controlling complex robotic systems in which optimal control problems are solved on board the robot at real-time rates. However, successful application of MPC depends critically on the performance of the algorithms used to solve th…
Planning trajectories for floating-base robotic systems that experience large attitude changes is challenging due to the nontrivial group structure of 3D rotations. This paper introduces a powerful and accessible approach for optimization-based planning on the space of rotations using only standard
Most approaches to multi-robot control either rely on local decentralized control policies that scale well in the number of agents, or on centralized methods that can handle constraints and produce rich system-level behavior, but are typically computationally expensive and scale poorly in the number
Trajectory optimization is a widely used tool for robot motion planning and control. Existing solvers for these problems either rely on off-the-shelf nonlinear programming solvers that are numerically robust and capable of handling arbitrary constraints, but tend to be slow because they are general…