Safety-Aware Optimal Scheduling for Autonomous Masonry Construction using Collaborative Heterogeneous Aerial Robots

2025-06-23

AI Summary

This work addresses the coupled challenges of mortar curing time constraints, structural dependencies, and multi-agent collision avoidance in heterogeneous aerial robot collaborative autonomous masonry. We propose a coordinated task planning framework integrating dynamic temporal constraints with spatial separation. Specifically, we formulate mortar curing deadlines and structural precedence requirements as precedence deadline constraints, embedded within a joint multi-UAV scheduling optimization. Coupled with spatiotemporal conflict detection and trajectory planning in Gazebo simulation, our approach ensures process compliance, safety, and operational efficiency in pipeline-style construction. Experiments demonstrate that the method significantly reduces construction duration, mitigates collision risk, and guarantees structural integrity and build quality. To the best of our knowledge, this is the first systematic solution to the triply coupled process–temporal–spatial constraints in autonomous aerial masonry.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Humans and AI: Planning and Decision Support for Human-Machine Teams

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Search and Retrieval-Augmented AI: Vertical and domain-specific search

Abstract

This paper presents a novel high-level task planning and optimal coordination framework for autonomous masonry construction, using a team of heterogeneous aerial robotic workers, consisting of agents with separate skills for brick placement and mortar application. This introduces new challenges in scheduling and coordination, particularly due to the mortar curing deadline required for structural bonding and ensuring the safety constraints among UAVs operating in parallel. To address this, an automated pipeline generates the wall construction plan based on the available bricks while identifying static structural dependencies and potential conflicts for safe operation. The proposed framework optimizes UAV task allocation and execution timing by incorporating dynamically coupled precedence deadline constraints that account for the curing process and static structural dependency constraints, while enforcing spatio-temporal constraints to prevent collisions and ensure safety. The primary objective of the scheduler is to minimize the overall construction makespan while minimizing logistics, traveling time between tasks, and the curing time to maintain both adhesion quality and safe workspace separation. The effectiveness of the proposed method in achieving coordinated and time-efficient aerial masonry construction is extensively validated through Gazebo simulated missions. The results demonstrate the framework's capability to streamline UAV operations, ensuring both structural integrity and safety during the construction process.

Problem

• Optimize UAV task allocation for masonry construction under curing deadlines
• Ensure safety constraints among parallel-operating heterogeneous aerial robots
• Minimize construction makespan while maintaining adhesion quality and workspace safety

Innovation

• Heterogeneous aerial robots for masonry tasks
• Dynamic scheduling with curing and safety constraints
• Optimized task allocation to minimize construction time