Autonomous robotic additive manufacturing through distributed model-free deep reinforcement learning in computational design environments.

ABSTRACT: The objective of autonomous robotic additive manufacturing for construction in the architectural scale is currently being investigated in parts both within the research communities of computational design and robotic fabrication (CDRF) and deep reinforcement learning (DRL) in robotics. The presented study summarizes the relevant state of the art in both research areas and lays out how their respective accomplishments can be combined to achieve higher degrees of autonomy in robotic construction within the Architecture, Engineering and Construction (AEC) industry. A distributed control and communication infrastructure for agent training and task execution is presented, that leverages the potentials of combining tools, standards and algorithms of both fields. It is geared towards industrial C

SUBMITTER: Felbrich B 

PROVIDER: S-EPMC9125977 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature