Task-Consistent Path Planning for Mobile 3D Printing

In this paper, we explore the problem of task-consistent path planning for printing-in-motion via Mobile Manipulators (MM). MM offer a potentially unlimited planar workspace and flexibility for print operations. However, most existing methods have only mobility to relocate an arm which then prints while stationary. In this paper we present a new fully autonomous path planning approach for mobile material deposition. We use a modified version of Rapidly-exploring Random Tree Star (RRT*) algorithm, which is informed by a constrained Inverse Reachability Map (IRM) to ensure task consistency. Collision avoidance and end-effector reachability are respected in our approach. Our method also detects when a print path cannot be completed in a single execution. In this case it will decompose the path into several segments and reposition the base accordingly

MAP - A Mobile Agile Printer Robot for on-site Construction

In this paper, we present a Mobile Agile Printer (MAP) construction robot; a highly agile, 4-legged, omnidirectional robot capable of 3D printing large structures. To overcome dynamic challenges when operating within an outdoors construction site, MAP incorporates a high-DoF 3D printing system connected to a mobile platform with novel features designed to enable disturbance rejection and live adaption to the robot's pose. In doing so, we demonstrate the benefits of designing construction robots with a focus on agility, a compact working volume and ability to operate within a potentially unlimited workspace. Performance tests were conducted showing smooth omni-directional motion as a key requirement for maintaining low 3D printing trajectory deviations over a large volume. In doing so, we show that MAP has the ability to construct in new ways more sensitive to its environment, context and concurrent on-site operations

YouWasps: Towards Autonomous Multi-Robot Mobile Deposition for Construction

Mobile multi-robot construction systems offer new ways to optimise the on-site construction process. In this paper we begin to investigate the functionality requirements for controlling a team of robots to build structures much greater than their individual workspace. To achieve these aims, we present a mobile extruder robot called YouWasp. We also begin to explore methods for collision aware printing and construction task decomposition and allocation. These are deployed via YouWasp and enable it to deposit material autonomously. In doing so, we are able to evaluate the potential for parallelization of tasks and printing autonomy in simulation as well as physical team of robots. Altogether, these results provide a foundation for future work that enable fleets of mobile construction systems to cooperate and help us shape our built environment in new ways