posted on 2024-02-09, 17:49authored byAlexander Hendrich, Daniel Kauth, Gregor H. W. Gebhardt, Kevin Daun, Marius Schnaubelt, Gerhard Neumann
<p>Large populations of simple robots can solve complex tasks, but controlling them is still a challenging problem, due to limited communication and computation power. In order to assemble objects, have shown that a human controller can solve such a task. Instead, we investigate how to learn the assembly of multiple objects with a single central controller. We propose splitting the assembly process in two sub-tasks -- generating a top-level assembly policy and learning an object movement policy. The assembly policy plans the trajectories for each object and the object movement policy controls the trajectory execution.The resulting system is able to solve assembly tasks with varying object shapes being assembled as shown in multiple simulation scenarios.</p>
History
School affiliated with
School of Computer Science (Research Outputs)
Publisher
international foundation for autonomous agents and multiagent systems
Date Submitted
2017-08-04
Date Accepted
2017-05-12
Date of First Publication
2017-05-12
Date of Final Publication
2017-05-12
Event Name
Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems (AAMAS 17)