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<p>New settlements in remote environments require terrain modification, a task well suited for autonomous multi-robot systems. Simple, robust earthmover robots offer an inexpensive and scalable alternative to sophisticated construction robots. We present a mathematical model for such robots modifying continuous granular structures in 2D and develop both centralized and decentralized planning algorithms to achieve user-defined construction goals. These algorithms decompose long-horizon tasks into subtasks solvable using optimal transport theory and Wasserstein geodesics. Simulations across 100 randomly generated tasks show that a centralized controller with global information achieves on average 85% and 92% construction progress on untraversable and traversable terrains respectively, even with action noise. Multiple robots reduce overall travel distance by 70%, important because motion over the structure also disturbs it. The distributed algorithm—without global information—matches centralized performance on traversable terrain, reaching 93% progress. Increasing robot numbers accelerates convergence, lowers moved material, and raises convergence rates, though congestion can increase total travel distance. These results indicate that simple earthmover robots hold promise for construction tasks ranging from extraterrestrial habitat preparation to coastal protective berms.</p>

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2D construction planning for swarms of simple earthmover robots

  • 期刊论文

  • 发表日期：

    2025年11月15日

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  • Jiahe Chen,
  • Kirstin Petersen

摘要

New settlements in remote environments require terrain modification, a task well suited for autonomous multi-robot systems. Simple, robust earthmover robots offer an inexpensive and scalable alternative to sophisticated construction robots. We present a mathematical model for such robots modifying continuous granular structures in 2D and develop both centralized and decentralized planning algorithms to achieve user-defined construction goals. These algorithms decompose long-horizon tasks into subtasks solvable using optimal transport theory and Wasserstein geodesics. Simulations across 100 randomly generated tasks show that a centralized controller with global information achieves on average 85% and 92% construction progress on untraversable and traversable terrains respectively, even with action noise. Multiple robots reduce overall travel distance by 70%, important because motion over the structure also disturbs it. The distributed algorithm—without global information—matches centralized performance on traversable terrain, reaching 93% progress. Increasing robot numbers accelerates convergence, lowers moved material, and raises convergence rates, though congestion can increase total travel distance. These results indicate that simple earthmover robots hold promise for construction tasks ranging from extraterrestrial habitat preparation to coastal protective berms.