Motion planning

Sharing the World with Autonomous Systems: What Goes Wrong and How to Fix It (NSF)

Develop efficient algorithms for autonomous systems to characterize and actively identify the inconsistencies (e.g., in perception and decision-making) among the interacting agents and to influence the behaviors of the other agents to improve the safety of the overall system.

CAREER: Establishing Correctness of Learning-Enabled Autonomous Systems with Conflicting Requirements (NSF)

Develop specification formalisms, control synthesis algorithms, and quantitative verification frameworks for autonomous systems that include learning-based components, operate in uncertain environments, and are subject to conflicting requirements with partially established priorities.

Planning with Conflicting Specifications

Develop planning and decision-making algorithms with multiple, potentially conflicting objectives.

Abstraction-Based Multi-Vehicle Command and Control

A path planning system for multi-vehicle domains.