Jong Jin Park, Collin Johnson, and Benjamin Kuipers. 2012.
Robot Navigation with Model Predictive Equilibrium Point Control.
IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2012.


An autonomous vehicle intended to carry passengers must be able to generate trajectories on-line that are safe, smooth and comfortable. Here, we propose a strategy for robot navigation in a structured, dynamic indoor environment, where the robot reasons about the near future and makes a locally optimal decision at each time step.

We propose the model predictive equilibrium point control (MPEPC) framework, in which the ideas of time-optimality and equilibrium point control are combined in order to generate solutions quickly and responsively.

Our approach depends on a carefully designed compact parameterization of a rich set of closed-loop trajectories, and the use of expected values in cost definitions. This allows us to formulate local navigation as a continuous, low-dimensional, and unconstrained optimization problem, which is easy to solve. We present navigation examples generated from real data traces.