Name
Abstract | ||
|---|---|---|
This letter proposes a novel Risk-Perception-Aware (RPA) control design using non-rational perception of risks associated with uncertain dynamic spatial costs. We use Cumulative Prospect Theory (CPT) to model the risk perception of a Decision Maker (DM) and use it to construct perceived risk functions that transform the uncertain dynamic spatial cost to deterministic perceived risks of a DM. These risks are then used to build safety sets which can represent risk-averse to risk-insensitive perception. Using these sets, we define novel notions of "inclusiveness" and "versatility" which can be employed to compare and evaluate any risk models in the context of RPA safety-critical controls. We then prove that CPT is the most "inclusive" and "versatile" model w.r.t. Conditional Value at Risk (CVaR) and Expected Risk (ER). Given a RPM, we construct a class of Control Barrier Functions (CBFs) and generate perceived-safety-critical controls using a Quadratic Program (QP) to guide an agent safely to a goal. For a class of truncated-Gaussian costs, we provide sufficient geometric conditions for the above QP to be feasible. We also prove that CPT-equipped RPA controller has both a larger feasible control set and more accurate stabilization w.r.t CVaR and ER models. We present simulations in a 2D environment to illustrate the proposed controller. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/LCSYS.2021.3134942 | IEEE CONTROL SYSTEMS LETTERS |
Keywords | DocType | Volume |
Costs, Safety, Control design, Uncertainty, Decision making, Sensitivity, Random variables, Risk-perception-aware controls, safety-critical controls, cumulative prospect theory, conditional-value at risk, risk perception models | Journal | 6 |
ISSN | Citations | PageRank |
2475-1456 | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aamodh Suresh | 1 | 0 | 0.68 |
| Sonia Mart ´ inez | 2 | 856 | 58.27 |