# Cooperative Aerial-Ground Multi-Robot System for Automated Construction Tasks

arXiv: https://arxiv.org/abs/2204.13926 · HTML: https://mlsanity.com/paper/2204.13926/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Apr 2022.

## Built on by (most cited first, 5 of 5)

- [An Efficient Ground-aerial Transportation System for Pest Control Enabled by AI-based Autonomous Nano-UAVs](https://mlsanity.com/paper/2502.14455/) (2025)
- [Generative Machine Learning in Adaptive Control of Dynamic Manufacturing Processes: A Review](https://mlsanity.com/paper/2505.00210/) (2025)
- [Drone Flocking Optimization using NSGA-II and Principal Component Analysis](https://mlsanity.com/paper/2205.00432/) (2022)
- [Autonomous Collaborative Scheduling of Time-dependent UAVs, Workers and Vehicles for Crowdsensing in Disaster Response](https://mlsanity.com/paper/2506.04276/) (2025)
- [Dual-Quadruped Collaborative Transportation in Narrow Environments via Safe Reinforcement Learning](https://mlsanity.com/paper/2602.16353/) (2026)

## Abstract (arXiv)

In this paper, we study a cooperative aerial-ground robotic team and its application to the task of automated construction. We propose a solution for planning and coordinating the mission of constructing a wall with a predefined structure for a heterogeneous system consisting of one mobile robot and up to three unmanned aerial vehicles. The wall consists of bricks of various weights and sizes, some of which need to be transported using multiple robots simultaneously. To that end, we use hierarchical task representation to specify interrelationships between mission subtasks and employ effective scheduling and coordination mechanism, inspired by Generalized Partial Global Planning. We evaluate the performance of the method under different optimization criteria and validate the solution in the realistic Gazebo simulation environment.