# Holistic Construction Automation with Modular Robots: From High-Level Task Specification to Execution

arXiv: https://arxiv.org/abs/2412.20867 · HTML: https://mlsanity.com/paper/2412.20867/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 58 references that are in the map.
- First posted on arXiv 30 Dec 2024.

## Builds on (most cited first, 12 of 12)

- [Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World](https://mlsanity.com/paper/1703.06907/) (2017)
- [Learning Dexterous In-Hand Manipulation](https://mlsanity.com/paper/1808.00177/) (2018)
- [Active Domain Randomization](https://mlsanity.com/paper/1904.04762/) (2019)
- [The Marathon 2: A Navigation System](https://mlsanity.com/paper/2003.00368/) (2020)
- [A Fully-Integrated Sensing and Control System for High-Accuracy Mobile Robotic Building Construction](https://mlsanity.com/paper/1912.01870/) (2019)
- [Mobile Manipulator for Autonomous Localization, Grasping and Precise Placement of Construction Material in a Semi-structured Environment](https://mlsanity.com/paper/2011.07972/) (2020)
- [Optimizing Modular Robot Composition: A Lexicographic Genetic Algorithm Approach](https://mlsanity.com/paper/2309.08399/) (2023)
- [CoBRA: A Composable Benchmark for Robotics Applications](https://mlsanity.com/paper/2203.09337/) (2022)
- [Timor Python: A Toolbox for Industrial Modular Robotics](https://mlsanity.com/paper/2209.06758/) (2022)
- [Open-Source, Cost-Aware Kinematically Feasible Planning for Mobile and Surface Robotics](https://mlsanity.com/paper/2401.13078/) (2024)
- [Design and Motion Planning for a Reconfigurable Robotic Base](https://mlsanity.com/paper/2206.15298/) (2022)
- [A perching and tilting aerial robot for precise and versatile power tool work on vertical walls](https://mlsanity.com/paper/2310.10548/) (2023)

## Built on by (most cited first, 1 of 1)

- [A Design Co-Pilot for Task-Tailored Manipulators](https://mlsanity.com/paper/2509.13077/) (2025)

## Abstract (arXiv)

In situ robotic automation in construction is challenging due to constantly changing environments, a shortage of robotic experts, and a lack of standardized frameworks bridging robotics and construction practices. This work proposes a holistic framework for construction task specification, optimization of robot morphology, and mission execution using a mobile modular reconfigurable robot. Users can specify and monitor the desired robot behavior through a graphical interface. In contrast to existing, monolithic solutions, we automatically identify a new task-tailored robot for every task by integrating acfbim. Our framework leverages modular robot components that enable the fast adaption of robot hardware to the specific demands of the construction task. Other than previous works on modular robot optimization, we consider multiple competing objectives, which allow us to explicitly model the challenges of real-world transfer, such as calibration errors. We demonstrate our framework in simulation by optimizing robots for drilling and spray painting. Finally, experimental validation demonstrates that our approach robustly enables the autonomous execution of robotic drilling.