The new analog: A protocol for linking design and construction intent with algorithmic planning for robotic assembly of complex structures

Construction robotics are increasingly popular in the architectural fabrication community due to their accuracy and flexibility. Because of their high degree of motion freedom, these tools are able to assemble complex structures with irregular designs, which advances architectural aesthetics and structural performance. However, automated task and motion planning (TAMP) for a robot to assemble non-repetitive objects can be challenging due to (1) a non-repetitive assembly pattern (2) the need for a continuous robotic motion throughout a sequence of movement (3) a congested construction scene and (4) occasional robot configuration constraints due to taught positions. Recent work has already begun to address these challenges for repetitive assembly processes, where the robot repeats a pattern of primitive behaviors (e.g. brick stacking or spatial extrusion). Yet, there are many assembly processes that can benefit from a non-repetitive pattern. For example, processes can change tools on an element-by-element level to accommodate a wider range of geometry. Our work is motivated by the necessity of robotic modeling and planning for a recently published timber assembly process which utilizes distributed robotic clamps to press together interlocking joints. In addition to pick-and-place operations, the robot needs to move numerous tools within the construction scene, similar to a tool-change operation. In order to facilitate an agile process for architectural design, construction process design, and TAMP, we introduce a flowchart-based specification language which allows various designers to describe their design and construction intent and knowledge. A compiler can then translate the assembly description, sequence, process flowchart, and robotic setup into a plan skeleton. Additionally, we present a linear and a non-linear solving algorithm that can solve the plan skeleton for a full sequence of robot motions. This algorithm can be customized to take into account designer intuition, which can speed up the planning process. We provide a comparison of the two algorithms using the timber assembly process as our case study. We validate our results by robotically executing and constructing a large-scale real-world timber structure. Finally, we demonstrate the flexibility of our flowchart by showing how custom assembly actions are modeled in our case study. We also demonstrate how other recently published robotic assembly processes can be formulated using our flowcharts to demonstrate generalizability.