Navid Dadkhah Tehrani — accepted AI-conference papers

2022

Multi-Objective Task Allocation for Multi-Agent Systems using Hierarchical Cost Function

Navid Dadkhah Tehrani, Andrew Krzywosz, Igor Cherepinsky, Sean Carlson

IROS 2022poster

Multi-agent systems are deployed to accomplish tasks that take a long time with a single agent. The task allocation problem becomes particularly difficult when the objectives are conflicting with one another (e.g. minimizing the mission time while respecting the task priorities, while simultaneously…

Cited by 3 Source ↗Scholar ↗

2021

Closed-loop Fast Marching Tree (CL-FMT*) with Application to Helicopter Landing Trajectory Planning

Navid Dadkhah Tehrani, Igor Cherepinsky, Sean Carlson

IROS 2021poster

Motion planning for complex dynamic systems such as helicopters is a challenging problem due to non-holonomic and nonlinear differential constraints. Approaches for optimal kinodynamics motion planning have only been demonstrated for simple dynamic systems such as Dubins car or linear systems. In th…

Cited by 3 Source ↗Scholar ↗