LegoBot: Automated Planning for Coordinated Multi-Robot Assembly of LEGO structures

Nägele, Ludwig; Hoffmann, Alwin; Schierl, Andreas; Reif, Wolfgang

doi:10.1109/iros45743.2020.9341428

Cited by 9 publications

(4 citation statements)

References 18 publications

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“…In contrast, we focus on planning for fixed-based robots working in crowded workspaces, in which finding jointly collisionfree paths is very challenging, prompting us to build on tools from multi-agent path finding. In a crowded assembly setting similar to ours, [9] plans for three fixed-base robot arms to assemble up to 32 bricks, but they are unable to plan collision-free asynchronous motion for the robots.…”

Section: Related Workmentioning

confidence: 99%

“…Several other planning systems for multi-arm assembly have been developed for assembling furniture [6], [7], construction architecture [8], and LEGO bricks [9]. In some systems [6], [7], robots are restricted to move sequentially when installing new components.…”

Section: Related Workmentioning

confidence: 99%

“…1, the robot on the right can only grasp object R from the top. If the MILP did not have constraint (9), the planner might assign this robot to assemble object R. However, since B, which is attached before R, blocks R from being top grasped, this task assignment admits no feasible motion plan. Indeed, in practice, without these constraints, the system fails to produce a solution for most assembly problems of interest.…”

Section: Task Assignmentmentioning

confidence: 99%

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Cooperative Task and Motion Planning for Multi-Arm Assembly Systems

Chen¹,

Li²,

Huang³

et al. 2022

Preprint

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Multi-robot assembly systems are becoming increasingly appealing in manufacturing due to their ability to automatically, flexibly, and quickly construct desired structural designs. However, effectively planning for these systems in a manner that ensures each robot is simultaneously productive, and not idle, is challenging due to (1) the close proximity that the robots must operate in to manipulate the structure and (2) the inherent structural partial orderings on when each part can be installed. In this paper, we present a task and motion planning framework that jointly plans safe, low-makespan plans for a team of robots to assemble complex spatial structures. Our framework takes a hierarchical approach that, at the high level, uses Mixed-integer Linear Programs to compute an abstract plan comprised of an allocation of robots to tasks subject to precedence constraints and, at the low level, builds on a state-of-the-art algorithm for Multi-Agent Path Finding to plan collision-free robot motions that realize this abstract plan. Critical to our approach is the inclusion of certain collision constraints and movement durations during high-level planning, which better informs the search for abstract plans that are likely to be both feasible and low-makespan while keeping the search tractable. We demonstrate our planning system on several challenging assembly domains with several (sometimes heterogeneous) robots with grippers or suction plates for assembling structures with up to 23 objects involving Lego bricks, bars, plates, or irregularly shaped blocks.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Task Assignmentmentioning

confidence: 99%

See 1 more Smart Citation

Cooperative Task and Motion Planning for Multi-Arm Assembly Systems

Chen¹,

Li²,

Huang³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Task and Motion Planning (TAMP) [9] is a standard framework to solve complex long-horizon robotic tasks, such as assembly [1], [10], object rearrangement [3], [11] and stacking [12]. Classical TAMP methods combine symbolic planning [13], [2] for sub-task decomposition and continuous-control methods for real robot execution [14].…”

Section: Related Workmentioning

confidence: 99%