Multi-Agent Systems Research

Towards Assume-Guarantee Profiles for Autonomous Vehicles

Rules or specifications for autonomous vehicles are currently formulated on a case-by-case basis, and put together in a rather ad-hoc fashion. As a step towards eliminating this practice, we propose a systematic method for ordering an autonomous vehicle's set of specifications so its decision-making process is both transparent and safe. Moreover, we introduce these profiles in the context of assume-guarantee profiles (behavioral contracts) that agents are expected to behave according to.

Rules of the Road: Towards Safety and Liveness Guarantees for Autonomous Vehicles

Publication shortly forthcoming.

Semantic Estimation Resesarch

Robust Estimation Framework with Semantic Measurements

Conventional simultaneous localization and mapping (SLAM) algorithms rely on geometric measurements and require loop-closure detections to correct for drift accumulated over a vehicle trajectory. Semantic measurements can add measurement redundancy and provide an alternative form of loop closure. We propose two different estimation algorithms that incorporate semantic measurements provided by vision-based object classifiers. An a priori map of regions where the objects can be detected is assumed.