IkeaBot: An autonomous multi-robot coordinated furniture assembly system

By Ross A. Knepper, Todd Layton, John Romanishin, Daniela Rus. 2013

210 citations recorded by the source corpus.

We present an automated assembly system that directs the actions of a team of heterogeneous robots in the completion of an assembly task. From an initial user-supplied geometric specification, the system applies reasoning about the geometry of individual parts in order to deduce how they fit together. The task is then automatically transformed to a symbolic description of the assembly-a sort of blueprint. A symbolic planner generates an assembly sequence that can be executed by a team of collaborating robots. Each robot fulfills one of two roles: parts delivery or parts assembly. The latter are equipped with specialized tools to aid in the assembly process. Additionally, the robots engage in coordinated co-manipulation of large, heavy assemblies. We provide details of an example furniture kit assembled by the system.

Subfields: Industrial and Manufacturing Engineering, Mechanical Engineering, Robotics & Control

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Citations in the corpus

Ego4D: Around the World in 3,000 Hours of Egocentric Video (2021, background): “[116] Ross A Knepper, Todd Layton, John Romanishin, and Daniela Rus.”
Asking for Help Using Inverse Semantics (2014, methodology): “Traditional methods for generating language rely on a dedicated language-generation system that is not integrated with a language-understanding framework [Jurafsky and Martin, 2008, Reiter and Dale, 2000].”
Learning Adaptive Language Interfaces through Decomposition (2020, background): “Other settings might include open-ended building tasks, either in the real world (Knepper et al., 2013; Lee et al., 2019), or in virtual worlds like Minecraft (Johnson et al.”
Autonomously constructing hierarchical task networks for planning and human-robot collaboration (2016, background): “a domain previously explored in multi-agent collaborative scenarios [32], as a statistical basis for the task structure.”
Effective robot teammate behaviors for supporting sequential manipulation tasks (2015, background): “The majority of multi-agent work within TAMP problems has focused on an ‘equal partners’ paradigm of teamwork, producing innovative solutions that rely on the decomposition of a task into subcomponents that can be distributed across agents to maximize efficiency and capability [10], [11], [12].”