Modeling Task Uncertainty for Safe Meta-Imitation Learning

To endow robots with the flexibility to perform a wide range of tasks in diverse and complex environments, learning their controller from experience data is a promising approach.In particular, some recent Walker/Rollator Accessories meta-learning methods are shown to solve novel tasks by leveraging their experience of performing other tasks during

read more

A Distributed Task Rescheduling Method for UAV Swarms Using Local Task Reordering and Deadlock-Free Task Exchange

Distributed task scheduling is an ongoing concern in the field of multi-vehicles, especially in recent years; UAV swarm performing complex tasks endows it with new characteristics, such as self-organization, scalability, reconfigurability, etc.This requires the swarm to have distributed rescheduling capability to dynamically include as many unassig

read more