Multi-Agent Collective Construction Using 3D Decomposition

Consider a Multi-Agent Collective Construction (MACC) problem that aims to generate a plan for fictitious cubic robots to build a three-dimensional structure comprised of cubic blocks. These cubic robots can carry one cubic block at a time; robots may move left, right, forwards, backward, or climb up or down one block. To construct structures taller than one cube, the robots must build supporting scaffolding made of blocks and remove the scaffolding once the structure is built. Prior works sought to create a planner that considered the structure as one monolithic assembly, which becomes intractable for larger workspaces and complex structures. To this end, we present a decomposition algorithm that breaks the structure into substructures that can be planned for independently. We use Mixed Integer Linear Programming (MILP) to plan for each of these substructures and then aggregate the solutions to construct the entire structure. Extensive testing on 200 randomly generated structures shows an order of magnitude improvement in the solution computation time compared to an MILP approach without decomposition. Finally, we leverage the independence between substructures to detect which substructures can be built in parallel.

Authors

• Akshaya Kesarimangalam Srinivasan
• Shambhavi Singh
• Geordan Gutow
• Howie Choset
• Bhaskar Vundurthy

Keywords

• Measurement
• Three-dimensional displays
• Aggregates
• Parallel processing
• Mixed integer linear programming
• Optimization
• Intelligent robots
• Computation Time
• Improvement In Time
• Order Of Magnitude Improvement
• Time Step
• Number Of Steps
• Parallelization
• Sequence Of Actions
• Reachable
• Random Structure
• Input Structure
• Number Of Time Steps
• Sum Of Costs
• Open-pit
• Swarm Robotics
• Structural Decomposition
• Percentage Of Occupancy