Risk-Sensitive Motion Planning using Entropic Value-at-Risk

Understand

We consider the problem of risk-sensitive motion planning in the presence of randomly moving obstacles.

• To this end, we adopt a model predictive control (MPC) scheme and pose the obstacle avoidance constraint in the MPC problem as a distributionally robust constraint with a KL divergence ambiguity set.
• This constraint is the dual representation of the Entropic Value-at-Risk (EVaR).
• Building upon this viewpoint, we propose an algorithm to follow waypoints and discuss its feasibility and completion in finite time.