Researchers at ETH Zurich teach a computer-controlled excavator the basic steps required to erect a simple drystone wall from thick boulders

Source: ETH Zürich

Automatic translation at the top of this web page under “English“

ETH Zurich researchers deployed an autonomous excavator, called HEAP, to build a six metre-high and sixty-five-metre-long dry-stone wall. Compared to normal drystone walls, it is a simple construction made of thick boulders which stonemasons couldn’t handle – but it is more than simply piling up the stones. The wall is embedded in a digitally planned and autonomously excavated landscape and park.

Using sensors, the excavator can autonomously draw a 3D map of the construction site and localise existing building blocks and stones for the wall’s construction.

Specifically designed tools and machine vision approaches enable the excavator to scan and grab large stones in its immediate environment. It can also register their approximate weight as well as their centre of gravity. An algorithm determines the best position for each stone, and the excavator then conducts the task itself by placing the stones in the desired location.

The autonomous machine can place 20 to 30 stones in a single consignment – about as many as one delivery could supply.

Source: ETH Zürich / Marc Schneider

The project was realized in cooperation of the National Centre of Competence in Research for Digital Fabrication (NCCR dfab) with Gramazio Kohler Research, the Robotics Systems Lab, Vision for Robotics Lab, and the ETH-Chair of Landscape Architecture. It was funded by Swiss National Centre of Competence in Research for Digital Fabrication, the European Space Agency, Eberhard Bau AG, ETH Zurich Foundation Partnership Council for Sustainable and Digital Construction, Siemens and Geberit.

Publication: Johns RL, Wermelinger M, Mascaro R, Jud D, Hurkxkens I, Vasey L, Chli M, Gramazio F, Kohler M, Hutter M: A framework for robotic excavation and drystone construction using on-site materials, Science Robotics, 22 November 2023
https://www.science.org/doi/10.1126/scirobotics.abp9758

ETH Zürich

See also:

(27.11.2023, USA: 11.27.2023)