Devadass, P; Stumm, S; Brell-Cokcan, S; (2019) Adaptive Haptically Informed Assembly with Mobile Robots in Unstructured Environments. In: Al-Hussein, M, (ed.) Proceedings of the 36th International Symposium on Automation and Robotics in Construction (ISARC 2019). (pp. pp. 469-476). International Association for Automation and Robotics in Construction (IAARC): Banff, Canada.

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Abstract

Robot assisted construction processes in the architectural domain which include assembly are uncommon due the size difference of the robot with respect the scale of the output. In order to extend the workspace of industrial robots, these can be mounted on top of a mobile platform. However industrial mobile robotics currently focuses on the utilization within clearly defined and structured production environments. Nevertheless, due to increasing product variety, a paradigm shift away from repetition of static task towards dynamic human robot collaboration is noticeable. Especially mobile robots face very specific challenges such as inaccuracy, dynamic on-site adaptability and predictability of whether the design is producible within the constraints of the robot. In this paper we discuss these challenges encountered due to onsite construction through a built project and illustrate the solution taken forward to address these challenges. In this research we propose a new methodology for on-site construction of non-standard components using mobile robots. The demonstrated project comprises of complex space frame timber system where every component of the structure is unique in its shape and size. For this we combine pre-planning of design with human-robot collaboration for on-site adaptation. The approach utilizes force torque sensors embedded within the robot in combination with haptic fiducials, in order to improving accuracy of the robotic fabrication and allow for human-robot collaboration within assembly. Employing the a-priori design knowledge the robot places the work-piece at the correct angle, while allowing for human adaptation of the path in order to increase accuracy. The paper illustrates the various optimization techniques developed to predict design manufacturability including potentially necessary adaptions. The research envisions a safe and automated large-scale construction methodology for complex systems and opens to new gateways for construction, allowing the collaboration between human workers and mobile robots within unstructured environments.

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