Robust Task and Motion Planning for Long-Horizon Architectural Construction Planning
This addresses the need for more efficient robotic systems in architectural construction, enabling faster design iterations for designers and engineers, though it appears incremental as it extends existing frameworks.
The paper tackles the problem of generic task-and-motion planning for long-horizon construction processes, which is beyond current capabilities, by developing a multi-agent TAMP framework that successfully constructs a large pavilion from hundreds of unique building elements autonomously.
Integrating robotic systems in architectural and construction processes is of core interest to increase the efficiency of the building industry. Automated planning for such systems enables design analysis tools and facilitates faster design iteration cycles for designers and engineers. However, generic task-and-motion planning (TAMP) for long-horizon construction processes is beyond the capabilities of current approaches. In this paper, we develop a multi-agent TAMP framework for long horizon problems such as constructing a full-scale building. To this end we extend the Logic-Geometric Programming framework by sampling-based motion planning,a limited horizon approach, and a task-specific structural stability optimization that allow an effective decomposition of the task. We show that our framework is capable of constructing a large pavilion built from several hundred geometrically unique building elements from start to end autonomously.